Numerical Design Tools Research Articles

Study of Electronic and Optical Properties of Low-Dimensional Nanosystems by First Principles Calculations

The development of new techniques for material manipulation at the nanoscale, as well as advanced numerical tools for material design, has opened up new prospects in the engineering of novel low-dimensional systems with properties specifically designed for applications in different fields, from photonics to energy conversion. Zero-, one-, and two-dimensional nanosystems show unique electronic, optical, and transport properties that can be tuned, for instance, by size reduction, passivation, and doping. In this talk, we discuss ab-initio results obtained in the study of structural, electronic, and optical properties of low-dimensional systems, in particular focusing on silicon, germanium, and silicon/germanium nanostructures. The analysis of mechanisms that can be exploited to tune Auger recombination and carrier multiplication processes, as well as of those that affect the formation of the band offset (Type I and Type II) at the nanoscale, will be discussed. At the end, effects induced by anion ordering on electronic and optical properties of metal oxynitrides will be analyzed.

An efficient frequency-domain based methodology for the preliminary design of FOWT substructures

An efficient frequency domain numerical tool for the preliminary design of the Floating Offshore Wind (FOW) substructures is developed, and validated against one of the leading state-of-the-art time domain based numerical tools: OpenFAST. It has been proven that the present tool enables to reach to similar conclusions as the state-of-the-art tools with a substantial reduction of the computational effort. This is achieved through two novel methods that obtain the hydrodynamic loads acting on the floating substructures. One estimates the linear hydrodynamic coefficients, and the other predicts the second-order wave loads. When combined with a simplified frequency domain response model, a quick assessment of the dynamics of numerous platform designs can be performed, accelerating the floater preliminary design process. The proposed method has been validated by carrying out a comparative analysis on a semi-submersible platform design space, characterised by the column diameter, the separation between the columns and the platform draft. The response motions have been compared against OpenFAST. Furthermore, the high efficiency of the proposed frequency domain tool makes it suitable to perform several sensitivity analyses that will allow for a better understanding of the dynamics and fine tune the foundations design accordingly from the early stages of design.

An experimental study on the aerodynamic loads of a floating offshore wind turbine under imposed motions

Abstract. The rotor of a floating wind turbine is subject to complex aerodynamics due to changes in relative wind speeds at the blades and potential local interactions between blade sections and the rotor near wake. These complex interactions are not yet fully understood. Lab-scale experiments are highly relevant for capturing these phenomena and provide means for the validation of numerical design tools. This paper presents a new wind tunnel experimental setup able to study the aerodynamic response of a wind turbine rotor when subjected to prescribed motions. The present study uses a 1:148 scale model of the DTU 10 MW reference wind turbine mounted on top of a 6 degrees of freedom parallel kinematic robotic platform. Firstly, the thrust variation of the turbine is investigated when single degree of freedom harmonic motions are imposed by the platform, with surge, pitch and yaw being considered in this study. For reduced frequencies greater than 1.2, it is found that the thrust variation is amplified by up to 150 % compared to the quasi-steady value when the turbine is subject to pitch and surge motions, regardless of the amplitude of motion. A similar behaviour is also noticed under yaw motions. Secondly, realistic 6 degrees of freedom motions are imposed by the platform. The motions are derived from FAST simulations performed on the full-scale turbine coupled with the TripleSpar floater, and the tests aim at exploring the thrust force dynamics for different sea states and wind conditions, obtaining reasonable agreement with the simulations. Finally, the work shows the capabilities of an off-the-shelf hexapod to conduct hybrid testing of floating offshore wind turbines in wind tunnels, as well as its limitations in performing such tests.

Sustainable space technologies—Strategies toward a predictive aerothermal design of re-useable space transportation systems

This paper presents a review of current aerothermal design and analysis methodologies for spacecraft. It briefly introduces the most important system architectures, including rockets, gliders, and capsule-based configurations, and gives an overview of the specific aerothermal and thermo-chemical effects that are encountered during their different flight phases and trajectories. Numerical and experimental design tools of different fidelity levels are reviewed and discussed, with a specific focus placed on the present limitations and uncertainty sources of models for the wide range of physical phenomena that are encountered in the analyses. This includes high temperature thermodynamics, chemical effects, turbulence, radiation, and gasdynamic effects. This is followed by a summary of current predictive capabilities and research foci, with missing capabilities identified. Finally, a future strategy toward an efficient and predictive aerothermal design of re-useable space transportation systems is proposed.

Validation and Assessment of a Hybrid VOF-Lagrangian Numerical Methodology for Turbulent Liquid Fuel Jets in High-Speed Crossflow

Abstract For gas turbine combustors, injecting liquid fuel in crossflow can achieve superior mixing characteristics to improve performance and reduce emissions. Robust numerical design tools are needed to accelerate the development of low-emissions technologies. Atomization modeling is often facilitated by using the Lagrangian approach rather than the more complex and computationally expensive Volume-of-Fluid (VOF) approach. However, most Lagrangian breakup models rely on empirical constants that must be fully calibrated for jets in crossflow and representative conditions. A hybrid approach could deliver a better compromise between accuracy and computational cost. This study proposes and validates a novel numerical methodology for coupling the VOF and Lagrangian approaches using a stochastic breakup model with Adaptive Mesh Refinements for turbulent liquid fuel jets in crossflow under more representative gas turbine conditions. The predictions were validated in the near and far-field regions using datasets at high pressures (1–8 bar), Weber numbers (720–1172), and momentum flux ratios (6–33). The predictive capabilities and computational cost were also compared to the Lagrangian approach coupled with large eddy simulations (LES) and with the unsteady Reynolds-Averaged Navier–Stokes (RANS) methodology previously developed and validated by the authors. The effect of different VOF-Lagrangian transition criteria on the computational cost was also assessed and recommendations were provided for further improvements. The overall LES predictions were significantly improved by the proposed hybrid methodology. Although it tends to underpredict the spray trajectory and Sauter Mean Diameter compared to the URANS methodology, it better captures the diameter in the wake region and the droplet velocities.

Multibody Dynamics Modeling of a Continuous Rubber Track System: Part 1—Model Description

<div>Continuous rubber track systems for farming applications are typically designed using multiple iterations on full-scale physical prototypes which is costly and time consuming. The development of numerical design tools could speed up the design process and reduce development costs while improving product performance. In this article, a rigid multibody dynamics (MBD) model of a continuous rubber track system is presented. This article is the first part of a two-part study: Part 1 focuses on the model description and part 2 describes the experimental evaluation of the MBD model. The modeling methodology is based on a track discretization as a set of rigid body elements interconnected by 6 degrees-of-freedom bushing joints. The mathematical formalism and experimental characterization of all critical subsystems such as the roller wheels, tensioner, suspensions, and contact models are also presented. Several simulation results are presented to illustrate the capability of MBD models in design activities to rapidly evaluate new concepts as a result of the relative short-solving time of the model (approximately 3 h). The MBD model is shown to be a powerful design tool to provide input boundary conditions for structural analysis or as a design space explorer and optimization tool.</div>

Model-Based Digital Overall Integrated Design Method of AUVs

Autonomous underwater vehicles (AUVs) have the characteristics of a high performance, a complex coupling mechanism, a compact, complex system composition, as well as high requirements for design constraints, quality, and reliability. In the traditional overall design process, numerous design tools and software programs are used, which results in poor model data sharing, a lack of uniqueness and synchronization between system levels, and difficulty in process tracing. Moreover, it is challenging to meet the technical requirements for close collaboration and rapid iteration of multiple positions. To address the aforementioned limitations, this study proposes a digital overall integrated design method for the design and simulation integration of AUVs and defines a unified architecture and interface for system-level design simulation models, thus solving the interoperability and consistency problems in multiple tools and models. In addition, a model-based AUV system integration design verification method that combines different processes, specifications, and models is designed, and software similar to Cameo, which can provide technical means for system-level integrated design and achieve rapid modeling and simulation verification based on system design solutions, is developed. Finally, a practical system design is conducted by taking specific AUV equipment as a research object, and the proposed methods are compared with traditional methods to prove the improvement effect of the technical route on the equipment and development efficiency.

Artificial intelligence (AI)-assisted simulation-driven earthquake-resistant design framework: Taking a strong back system as an example

Traditional earthquake-resistant structural design considers only a limited number of factors, mainly elastic structural properties, to determine key design parameters. However, these parameters are often not optimal because they do not take into account the extensive plasticity expected in building structures during earthquakes. To address this issue, an artificial intelligence (AI)-assisted simulation-driven framework has been developed in this study. This framework can automatically output optimal design parameters while considering nonlinear structural response under strong earthquakes and a large number of input factors. The primary innovation of the proposed framework lies in the fusion and integration of nonlinear numerical simulation and AI tools for earthquake-resistant design of building structures, marking a promising trend in this field. The framework consists of two steps. In the first step, a database that consists of optimal design parameters and covers a wide range of design inputs will be created through numerical nonlinear response history analyses (NRHAs). In the second step, AI models will be created and trained based on the database to automatically output the optimal design parameters. To illustrate the basic components underlying the proposed framework, the determination of the height-wise distribution (denoted by Ψ) of the total design lateral force for a strong back system is taken as an example. A database of 1200 samples was created through NRHAs, and an artificial neural network (ANN) model was created, optimised, and trained. The developed ANN model yielded optimal Ψ with the majority of absolute errors within 1%, demonstrating the feasibility of the proposed AI-assisted simulation-driven earthquake-resistant design framework.

Efficient hydrodynamic analysis for preliminary design of Floating Offshore Wind substructures

The cost of Floating Offshore Wind (FOW) is driven by the foundation, thus it can be reduced by optimising the floater design from the early stage. Most of the numerical tools for the platform design integrate radiation–diffraction theory-based software, but it can make the whole process very time-consuming since the preliminary design phases usually imply the analysis of a large number of designs. In order to accelerate the first stages of design, and consequently, achieve the foundation cost reduction, this study proposes an efficient methodology for the hydrodynamic added mass, radiation damping, and excitation loads calculation. The method is implemented for a semi-submersible platform, and it is verified against the radiation–diffraction commercial software AQWA. The methodology is validated through a comparative analysis of the response of ten different platforms, and it has shown that the hydrodynamic coefficients derived from either radiation–diffraction analysis or from the proposed method lead to equivalent conclusions. The maximum values of the platform’s pitch angle and the nacelle acceleration are assessed, achieving a maximum deviation among the most critical designs of 3% and 17%, respectively. This methodology has demonstrated to provide with reasonable accuracy the dynamic behaviour of the offshore wind substructures achieving a significant computational cost reduction compared to the state-of-the-art methods, which enables to accelerate the optimisation process and thus, resulting in a more accurate floater preliminary design.

Enabling Floating Offshore VAWT Design by Coupling OWENS and OpenFAST

Vertical-axis wind turbines (VAWTs) have a long history, with a wide variety of turbine archetypes that have been designed and tested since the 1970s. While few utility-scale VAWTs currently exist, the placement of the generator near the turbine base could make VAWTs advantageous over tradition horizontal-axis wind turbines for floating offshore wind applications via reduced platform costs and improved scaling potential. However, there are currently few numerical design and analysis tools available for VAWTs. One existing engineering toolset for aero-hydro-servo-elastic simulation of VAWTs is the Offshore Wind ENergy Simulator (OWENS), but its current modeling capability for floating systems is non-standard and not ideal. This article describes how OWENS has been coupled to several OpenFAST modules to update and improve modeling of floating offshore VAWTs and discusses the verification of these new capabilities and features. The results of the coupled OWENS verification test agree well with a parallel OpenFAST simulation, validating the new modeling and simulation capabilities in OWENS for floating VAWT applications. These developments will enable the design and optimization of floating offshore VAWTs in the future.

A dual‐scale three‐dimensional thermo‐viscoelastic model for the hot stamping simulation of thermoplastic composites

AbstractExisting hot stamping simulations are performed at the macroscopic scale, making optimizing process parameters for a new composite system time‐consuming. This paper develops a dual‐scale three‐dimensional thermos‐viscoelastic model based on a numerical homogenization approach to accurately predict the structural deformation of thermoplastic composite laminates during hot stamping. The viscoelastic homogenization model is developed on representative volume elements using temperature‐dependent viscoelastic parameters determined from thermo‐mechanical tests. The effective properties of the composites are identified from the homogenization results, which are then combined with the experimentally measured thermal behavior into a numerical model of the hot stamping process. The developed model is validated by the agreement between the finite element homogenization results and the predictions made using the determined parameters. The simulated warpage of the molded part also agrees well with the experimental measurements. The developed dual‐scale model can be used to predict the effective thermomechanical properties of composites. Moreover, it can also be integrated into numerical tools for structural design and process optimization of thermoplastic composites.

Modelling edge effects at the interface in bonded joints using gradient functions in the mechanical properties of the adhesive: Application of the method to the Arcan test loaded in tension and shear

The design of bonded joints requires studies of stress concentrations due to edge effects. For complex joint configurations, the finite element method can be quite costly. The objective is to develop a fast and reliable numerical design tool for bonded assemblies. Therefore, an approach to design bonded assemblies is presented which aims to meet the needs of a design office, particularly in terms of calculation costs. The latter consists in reproducing the edge effects with a single element through the joint thickness using a modulus function. The concept was tested on Arcan specimen with two loading cases: tension (γ = 0°) and shear (γ = 90°). A 2D model under the elastic assumption is developed to describe the edge effects of the joint using Abaqus subroutines (UMat). The approach is set up to solve this problem in the form of two blocks. First, mesh refinement studies for bonded specimens loaded in tension were performed, within a good level of accuracy, on the free edge with the use of local discretization error estimation. After that, the effects of local geometry and modulus ratio are investigated. Afterwards, the von Mises stress at the interface level of the adhesive joint was used to identify a modulus function to describe the behavior of a joint with straight edge geometry for tension and shear loadings. The proposed approach has improved the performance of the model. Actually, the calculation is practically three times faster than for the conventional model.

Solar tree-based water pumping for assured irrigation in sustainable Indian agriculture environment

Solar power irrigation systems have been widely employed in many countries to enhance access to electricity for irrigation, and numerous design tools have been developed for better performance and implementation. The findings are based on the quantitative analysis that predicts the water requirements for horticultural crops as their behavior is dynamic throughout the year and different cycles need surplus electrical energy requirements that can be transferred under different loads after irrigation. The research article emphasizes the techno-economic analysis, which is carried out to suggest the minimum cost prediction based on the data processing and analysis. The data collection is based on the number of days required in different horticulture crop cycles, and different development stages for water requirements. The water requirements in the different development stages are 9.30, 13.98, 27.90, and 27.31 mm/day for initial (20 days), development (30 days), mid-season (40 days), and late-season (25 days) respectively. The estimated CO 2 mitigation values are 2170, 25.00, 0.9832, and 53,339 based on the yearly electricity harvest (kWh), lifetime (years), Kaya identity (kgCO 2 /kWh), and carbon dioxide for life span (kgCO 2 /kWh) respectively. The estimated cost of a solar tree-based irrigation system is $3430, which suggests the techno-economic behavior of Indian rural application to carry sustainable agriculture in India. If users can change their methods to use alternate energy technology, it may save money on energy and reduces their dependability on the grid energy.

Multi-configuration evaluation of a megajoule-scale high-temperature latent thermal energy storage test-bed

Thermal energy storage via latent heat provides an energy dense solution and, during discharge, a hot stream at a well-defined temperature. Utilizing metal phase change materials (PCMs) and high-temperature operation might enable fast (dis)charging and application in previously unexplored areas (e.g. high-temperature processing industry). But detailed characterization and design guidelines of high-temperature metal latent heat storage systems with tailored characteristics are missing. Here, we introduce a combined experimental–numerical characterization and design tool for high-temperature heat storage units. We apply it to a megajoule-scale test-bed operated with steel encapsulated Al68.5Cu26.5Si5 (weight%) (melting temperature 791K) as the PCM and air as heat transfer fluid (HTF) for charging and discharging. Thermocouples positioned at multiple locations throughout the storage unit are used to characterize the performance and heterogeneity. For the inaugural experimental campaign, three encapsulated tubes with a total of 1.83kg PCM were vertically arranged in one of the modular stacks and several multi-hour charging/discharging cycles were performed with the HTF heated up to 30−70K above and below the PCM melting point at a flow rate of 1500lmin−1. Specifically designed open-cell cellular Si-SiC lattices were wrapped around the PCM tubes to enhance the heat transfer. The experimental results showed a near-isothermal (±10K) exit temperature discharge maintained for 0.39 - 2.67 h. Temperature variations throughout the test-bed indicated that test-bed design is important to ensure homogeneous usage of the PCM and controlled phase change. A quasi-1D lumped parameter multi-mode heat transfer model was developed to quantify the thermal stratification within the PCM, heat losses, and phase change characteristics in the thermal storage, and provided explanation and quantification for the experimentally observed heterogeneities. The model was used to extrapolate the heat storage characteristics to larger scales: a 16.84MJ and 50.51MJ latent heat storage with the modular stacks filled with 25.7kg (42 encapsulated tubes) and 77kg (126 encapsulated tubes) of the PCM, respectively. The coupled experimental–numerical approach allowed for model validation, explanation of experimental variation, and to provide general design guidelines for practically relevant latent high-temperature (metal) thermal energy storage.

ESTUDIO CFD DE PÉRDIDA DE CARGA EN VÁLVULA DE TESLA T45-R

The Tesla valve is a check valve without moving parts. Its operation depends strongly on the flow rate. This conduit develops asymmetric head losses due to its geometric design, behaving like a hydraulic diode with a certain degree of efficiency. In the direct flow direction, the pressure drop is relatively low, while in the reverse direction the hydraulic resistance is higher. In the present work, we develop a numerical model, based on Computational Fluid Dynamics(CFD), to study the normalized Tesla valve T45-R. We simulate the incompressible laminar flow in this device. First, we analyze the precision of the model with a mesh convergence analysis. Subsequently, we compared the numerical prediction of head loss with experimental data for low Reynolds numbers, obtaining good agreement. We observe differences of less than 15 % for the forward direction and less than 6 % for the reverse direction. The diodicity prediction of the CFD differs from the experimental data below 5 %. The results obtained from the loss coefficient K differ from the experimental data by less than 14 %. Afterwards, we compared the CFD results with 0D models, available in the literature, observing a good agreement for a wider Reynolds number range. As a result of this study, we have a numerical design tool for this type of device, particularly applied in the field of microfluidics, having verified its precision in a wide operating range.

CaSilico: A versatile CRISPR package for in silico CRISPR RNA designing for Cas12, Cas13, and Cas14.

The efficiency of the CRISPR-Cas system is highly dependent on well-designed CRISPR RNA (crRNA). To facilitate the use of various types of CRISPR-Cas systems, there is a need for the development of computational tools to design crRNAs which cover different CRISPR-Cas systems with off-target analysis capability. Numerous crRNA design tools have been developed, but nearly all of them are dedicated to design crRNA for genome editing. Hence, we developed a tool matching the needs of both beginners and experts, named CaSilico, which was inspired by the limitations of the current crRNA design tools for designing crRNAs for Cas12, Cas13, and Cas14 CRISPR-Cas systems. This tool considers a comprehensive list of the principal rules that are not yet well described to design crRNA for these types. Using a list of important features such as mismatch tolerance rules, self-complementarity, GC content, frequency of cleaving base around the target site, target accessibility, and PFS (protospacer flanking site) or PAM (protospacer adjacent motif) requirement, CaSilico searches all potential crRNAs in a user-input sequence. Considering these features help users to rank all crRNAs for a sequence and make an informed decision about whether a crRNA is suited for an experiment or not. Our tool is sufficiently flexible to tune some key parameters governing the design of crRNA and identification of off-targets, which can lead to an increase in the chances of successful CRISPR-Cas experiments. CaSilico outperforms previous crRNA design tools in the following aspects: 1) supporting any reference genome/gene/transcriptome for which an FASTA file is available; 2) designing crRNAs that simultaneously target multiple sequences through conserved region detection among a set of sequences; 3) considering new CRISPR-Cas subtypes; and 4) reporting a list of different features for each candidate crRNA, which can help the user to select the best one. Given these capabilities, CaSilico addresses end-user concerns arising from the use of sophisticated bioinformatics algorithms and has a wide range of potential research applications in different areas, especially in the design of crRNA for pathogen diagnosis. CaSilico was successfully applied to design crRNAs for different genes in the SARS-CoV-2 genome, as some of the crRNAs have been experimentally tested in the previous studies.

A diffuse interface method for solid-phase modeling of regression behavior in solid composite propellants

Solid composite propellants (SCPs) are ubiquitous in the field of propulsion. In order to design and control solid rocket motors, it is critical to understand and accurately predict SCP regression. Regression of the burn surface is a complex process resulting from thermo-chemical-mechanical interactions, often exhibiting extreme morphological changes and topological transitions. Diffuse interface methods, such as phase field (PF), are well-suited for modeling processes of this type, and offer some distinct numerical advantages over their sharp-interface counterparts. They also provide a convenient framework for incorporating multiple multiphysical dynamics. In this work, we present a phase-field method for modeling the regression of SCPs with varying species and geometry. We construct the model from a thermodynamic perspective, leaving the base formulation general. A diffuse-species-interface field is employed as a mechanism for capturing complex burn chemistry in a reduced-order fashion, making it possible to model regression from the solid phase only. The computational implementation, which uses block-structured adaptive mesh refinement and temporal substepping for increased performance, is briefly discussed. The model is then applied to four test cases: (i) pure AP monopropellant, (ii) AP PBAN sandwich, (iii) AP HTPB sandwich, and (iv) spherical AP particles packed in HTPB matrix in two and three dimensions. In all cases, reasonable quantitative agreement is observed, even when the model is applied predictively (i.e., no parameter adjustment), as in the case of (iv). The validation of the proposed PF model demonstrates its efficacy as a numerical design tool for future SCP investigation.

Electromagnetic field/hypersonic flow field coupled algorithm and its application in the magnetic controlled inlet design

A novel magnetic controlled inlet design method is proposed for the airbreathing hypersonic vehicles cruising at an extremely high Mach number. By introducing the electromagnetic source terms to the Euler equations, an electromagnetic field/hypersonic flow field coupled algorithm is developed as the numerical design tool. A quasi-one-dimensional simplified model of the magnetic controlled inlet is constructed to analyze the compression performance under the different combinations of magnetic field and leading-edge shock angle. The results show that the combination of weak leading-edge shock and strong magnetic field can obtain a better compression effect. Three inlets are designed under the magnetic field with the induction intensity of 0.05 T, 0.08 T, and 0.1 T, respectively. The designed inlets have a contraction ratio of nearly 1.5 and the wall shape is not sensitive to the variation of magnetic induction intensity. With an inflow Mach number of 10, the exit Mach number can be reduced from 5 to 2.5 when the magnetic induction intensity is adjusted from 0.05 T to 0.1 T. In addition, there is no reflected shock in the inner channel of the inlet and therefore the complex shock/boundary layer interaction in the conventional inlet has been greatly relieved. Although the total pressure recovery is significantly reduced, part of the energy loss can be transformed to electric energy by the MHD energy extraction equipment and used to accelerate the nozzle flow.

A simplified modal analysis of a single lap bonded joint using the macro-element technique

Modal analyses are essential steps in structural design. Simple and quick numerical procedures and design tools for modal and dynamic analysis of bonded joints would be an attractive option to increase the efficiency of the design process in its early phases. This paper offers a simple and quick numerical tool dedicated to the modal analysis of single lap bonded joints with balanced and unbalanced adherends with various boundary conditions. Based on the macro-element technique developed with Taylor expansion in power series, this paper gives all the steps to develop the mass matrix associated with a macro-element. The mass matrix has been developed so far for 1D-bar and 1D-beam kinematic frameworks. The results obtained with the macro-element technique and a Finite Element analysis give similar results.

Numerical simulation methods for motion-induced eddy current testing signals based on Ar formulation and edge finite elements

In this paper, numerical methods for simulation of the motion-induced eddy current testing (MIECT) signals were developed based on the reduced magnetic vector potential formulation (Ar method) and the edge finite element. According to the principle of the MIECT problem, numerical methods with reference frame referring to the transducer or the inspection object were developed respectively to solve the eddy current and pickup magnetic field signals. In addition, a quasi-static numerical scheme was also adopted to simulate the MIECT problem for inspecting crack along the moving direction. Based on the proposed numerical schemes and the conventional Ar code, numerical programs of the 3 methods were developed and validated for simulating MIECT signals. Through comparing the numerical results and efficiencies of the three simulation schemes each other, the validity of the proposed methods and the corresponding numerical codes were theoretically verified at first. Then, a MIECT experimental system and a prototype probe were developed and the validity of the proposed numerical methods were further proved experimentally. It is found that the moving probe-fixed object method is the most efficient scheme for MIECT signal simulation among the three proposed numerical methods. The numerical methods and codes developed in this paper provide numerical tools for design and optimization of the MIECT probes and testing system used in inspection of rails or wheels system etc, as well as the quantitative defect evaluation based on the MIECT signals through model based inverse analyses.