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Mahmoud Elkafafy

Mahmoud Elkafafy
Siemens Industry Software NV · TEST Division | Leuven | Belgium

PhD degree

About

50
Publications
20,691
Reads
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506
Citations
Citations since 2016
23 Research Items
383 Citations
20162017201820192020202120220102030405060
20162017201820192020202120220102030405060
20162017201820192020202120220102030405060
20162017201820192020202120220102030405060
Introduction
Mahmoud received his Bachelor/Master degrees from Helwan university / Egypt in Mechanical power engineering. He got his PhD degree from Vrije Universiteit Brussel (VUB) in 2013 in mechanical engineering. Then, he started a post-doc position at VUB in a close collaboration with Siemens Industry Software (SISW) from 2014 until 2018. He is currently working as a research engineer advanced at SISW. His main research interests are: system identification techniques, Machin learning, modal analysis.
Additional affiliations
April 2009 - present
Vrije Universiteit Brussel (VUB)
Position
  • PostDoc Position
Description
  • Mahmoud obtained his PhD degree from Vrije Unversiteit Brussel in 2013 with greatest distinction and was soon after granted an IWT innovation mandate position to continue his research on a post-doctoral level.
April 2009 - December 2015
Vrije Universiteit Brussel
Position
  • PostDoc Position

Publications

Publications (50)
Chapter
As systems become more and more complex, representing them with differential equations or transfer functions becomes cumbersome and even more so if the number of inputs and outputs are growing. Using a state space model representation largely alleviates this problem as it provides a convenient and compact way to model and analyze MIMO systems. In v...
Conference Paper
This paper presents a new method for automated tuning of Kalman based virtual sensors. Such virtual sensors use a Kalman filter to estimate non-measured quantities, based on measured data and a model. In order to achieve optimum accuracy, one must characterize the model prediction errors and the measurement errors by means of their respective covar...
Conference Paper
Historically, simulations of the vibro-acoustic of products have been mainly performed in the frequency domain. Especially for damping, a key characteristic of vibro-acoustic systems, dedicated modelling formalisms exist (e.g. Perfectly/Automatically Matched Layer (P/AML) to account for unbounded domains, or dedicated frequency-dependent damping ma...
Conference Paper
This paper presents a physics-based virtual sensing approach to estimate the full-field pressure responses during direct field acoustic excitation testing (DFAX) through MIMO random control. It makes use of a system level physics based model that consists of an electro-mechanical lumped parameter model of the speaker and a finite element model to d...
Conference Paper
Full-text available
This paper introduces machine learning (ML)-based identification of data-driven virtual channels to predict vehicle dynamics and durability-related quantities that require instrumentation of expensive and/or hard-to-install sensors (e.g., wheel force transducers) when performing a proving ground track test to characterize both the ride & handling d...
Conference Paper
Full-text available
In this paper, we are investigating the capabilities of both classical system identification and modern machine learning (time regression neural networks) to derive predictive black-box models which can predict the wheel center loads (WCLs) by making use of either the road disturbances acting on the wheel-patch or strain measurements on the suspens...
Article
Full-text available
Recently, a lot of efforts have been devoted to developing more precise Modal Parameter Estimation (MPE) techniques. This is explained by the necessity in civil, mechanical and aerospace engineering of obtaining accurate estimates for the modal parameters of the tested structures, as well as of determining reliable confidence intervals for these es...
Article
In this paper, a new feature added to the MLMM modal parameter estimation method (Maximum Likelihood estimation of a Modal Model) will be introduced. The MLMM method tackles some of the remaining challenges in modal analysis, e.g. modal analysis of highly-damped cases where a large amount of excitation locations is needed such as the modal analysis...
Article
Full-text available
In this paper, a full Acoustic Modal Analysis (AMA) procedure to improve the CAE predictions of the car interior noise level is proposed. Some of the challenges that can be experienced during such an analysis are described and new solutions to face them are proposed. Particular AMA challenges range from the arrangement of the experimental setup to...
Conference Paper
Full-text available
In modal identification, the value of the model parameters and the associated uncertainty depends on the quality of the measurements. The maximum likelihood estimator (mle) is a consistent and efficient estimator. This means that the value of the parameters trends asymptotically close to the true value, while the variance of such parameters is the...
Conference Paper
Full-text available
Traditionally, modal parameters are experimentally extracted from FRFs measured in laboratory conditions. However, most of the real structures (e.g. bridges, in-flight testing of aircrafts) have to be tested in their real operational conditions rather than the laboratory conditions; this is called operational modal analysis (OMA). In OMA, the real...
Conference Paper
Full-text available
Whereas the experimental identification of modal models of car bodies in white is a well-established process both on the level of measurement procedures and modal analysis, this is much less the case when dealing with trimmed car bodies. The high amount of damping necessitates the use of many excitation locations, which on its turn makes the identi...
Article
Full-text available
An offshore wind turbine (OWT) is a complex structure that consists of different parts (e.g., foundation, tower, drivetrain, blades, et al.). The last decade, there has been continuous trend towards larger machines with the goal of cost reduction. Modal behavior is an important design aspect. For tackling noise, vibration, and harshness (NVH) issue...
Chapter
Offshore Wind Turbine (OWT) is complex structure that consists of different parts (e.g. foundation, tower, drivetrain, blades, …). The last decade there is a continuous trend towards larger machines with the goal of cost reduction. Modal behavior is an important design aspect. For tackling NVH issues and validating complex simulation models it is o...
Chapter
In this paper, the recently-developed MLMM method (Maximum Likelihood estimation of a Modal Model) will be introduced and applied to challenging industrial cases. Specific about the method is that the well-established statistical concept of maximum likelihood estimation is applied to estimate directly a modal model based on measured Frequency Respo...
Conference Paper
Full-text available
In this paper, a full Acoustic Modal Analysis (AMA) procedure to improve the CAE predictions of the car interior noise level is proposed. Some of the challenges that can be experienced during such an analysis are described and new solutions to face them are proposed. Particular AMA challenges range from the arrangement of the experimental setup to...
Conference Paper
Full-text available
In engineering practice, there is a great interest to determine vibro-acoustic characteristics of structures by means of experimentally driven modal models. To make these modal models usable for the intended application, they have to verify some constraints defined by the modal theory (e.g. FRFs reciprocity, real mode shapes...). Rarely, modal para...
Article
Composite materials are nowadays widely used in several applications, especially in the aerospace field. Despite the numerous advantages that composites can offer, the health monitoring of this type of structures is challenging. A major challenge regards the detection and monitoring of delaminations. In the case of aeronautical structures, delamina...
Article
Recently, a new maximum likelihood modal model-based (ML-MM) modal parameter estimator has been proposed [1,2]. One major drawback of this estimator is the modeling error, which can be caused by the effects of out-of-band modes (i.e. lower and upper residual effects). The ML-MM estimator uses the modal model as a parameterization form. This modal m...
Article
A new modal parameter estimation method to directly establish modal models of structural dynamic systems satisfying two physically motivated constraints will be presented. The constraints imposed in the identified modal model are the reciprocity of the frequency response functions (FRFs) and the estimation of normal (real) modes. The motivation beh...
Conference Paper
Full-text available
The identification of system parameters using forward approaches is not always practical due to the rising complexity of modern structures, leaving no chance for direct parameter measurements. In contrast to forward methods, inverse techniques have been gaining popularity, since the advent of high performing computers. This approach consists of the...
Article
Full-text available
In the automotive industry, one of the most important comfort requirements in designing a high quality vehicle is to avoid or minimize the noise in the passenger compartment. Therefore, an ever increasing interest exists to predict the interior acoustic behavior by means of accurate simulation models both to improve the vehicle NVH performance and...
Article
Full-text available
In this paper, the applicability of Particle Swarm Optimization (PSO) to identify the modal parameters will be tested. PSO is a heuristic optimization method which does not require the calculation of the error derivatives with respect to the model parameters hence the Jacobian matrix formulation is not required. The modal parameters will estimated...
Chapter
Full-text available
In this paper, the ML-MM estimator, a multivariable frequency-domain maximum likelihood estimator based on a modal model formulation, will be represented and improved in terms of the computational speed and the memory requirements. Basically, the design requirements to be met in the ML-MM estimator were to have accurate estimate for both of the mod...
Conference Paper
Full-text available
The key challenge behind the Polymax Plus modal parameter estimator is to keep the property of clear stabilization diagram constructed by the well-known Polymax estimator (Polymax user friendliness) and at the same time to have improved, statistically optimal, modal parameter estimates (Maximum likelihood (ML) accuracy). The Polymax Plus estimator...
Conference Paper
Full-text available
The interior sound perceived in an automotive cabin is a very important attribute in vehicle engineering. Therefore, an industrial interest exists to predict the acoustic behaviour with simulation models. To understand the modelling challenges and improve the modelling know-how, experimental acoustic methods play an important role. Also for trouble...
Article
Full-text available
This study shows the first results of a long-term monitoring campaign on an offshore wind turbine in the Belgian North Sea. It focuses on the continuous monitoring of the resonant frequencies and damping values of the most dominant modes of the support structure. These parameters allow to better understand the dynamics of offshore wind turbines and...
Conference Paper
Full-text available
This paper will evaluate different automated operational modal analysis techniques for the continuous monitoring of offshore wind turbines. The experimental data has been obtained during a long-term monitoring campaign on an offshore wind turbine in the Belgian North Sea. State-of-the art operational modal analysis techniques and the use of appropr...
Conference Paper
Full-text available
As all experimental procedures, Experimental Modal Analysis (EMA) is subject to a wide range of potential testing and processing errors. The modal identification methods are sensitive to these errors, yielding modal results which are uncertain up to certain error bounds. The question hence is what these error bounds on test data and modal parameter...
Article
Recently, a new maximum likelihood modal model-based (ML-MM) modal parameter estimator has been proposed [1, 2]. One major drawback of this estimator is the modelling error, which can be caused by the effects of out-of-band modes (i.e. lower and upper residual effects). The ML-MM estimator uses the modal model as a parameterization form. This modal...
Article
Full-text available
This paper will show the first results of a long term monitoring campaign on an offshore wind turbine in the Belgian North Sea. It will focus on the vibration levels and resonant frequencies of the fundamental modes of the support structure. These parameters will be crucial to minimize O&M costs and to extend the lifetime of offshore wind turbine s...
Conference Paper
Full-text available
Future Offshore Wind Turbines will be hardly accessible; therefore, in order to minimize O&M costs and to extend their lifetime, it will be of high interest to continuously monitor the vibration levels and the evolution of the frequencies and damping ratios of the first modes of the foundation and tower structures. Wind turbines are complex structu...
Conference Paper
Full-text available
In this paper, a multivariable frequency-domain maximum likelihood estimator based on a modal model formulation is proposed. The proposed approach is mainly introduced to improve the accuracy of the modal parameters estimated by the poly-reference least squares complex frequency-domain (i.e. pLSCF) estimator and to have their confidence intervals a...
Conference Paper
Full-text available
The poly-reference Least Squares Complex Frequency-domain (pLSCF) estimator –commercially known as the LMS PolyMAX method- has introduced an improvement in the field of modal analysis. The main advantages are its computational speed and the very clear stabilization diagrams it yields even in the case of highly damped systems and noisy FRF measureme...
Article
Full-text available
In this paper, the performance of automotive ride comfort using Bouc-Wen type magneto-rheological (MR) fluid damper is studied using a two degree of freedom quarter car model. The sliding mode control is used to force the MR damper to follow the dynamics of ideal sky-hock model. The model is tested on two excitations, the first is a road hump with...
Article
The object of this paper is to introduce a new technique to derive the global modal parameter (i.e. system poles) directly from estimated matrix orthogonal polynomials. This contribution generalized the results given in Rolain et al. (1994) [5] and Rolain et al. (1995) [6] for scalar orthogonal polynomials to multivariable (matrix) orthogonal polyn...
Article
In this paper, the performance tradeoffs in the design of electronically controlled suspension systems are theoretically studied. Using quarter car model, a new treatment procedure for the control laws is introduced using fully active suspension system with two control strategies. The first strategy is considered for vehicle vibration isolation due...

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Projects (3)
Project
The general objective of this project is to develop industrial non-destructive testing (NDT) techniques for damage and defect detection and characterization in composite and 3D-printed structures. The proposed methodologies aim at bringing together innovations in excitation, sensing, digital data processing and numerical modeling.
Project
It was observed that classical modal parameters estimation techniques (e.g. Polymax, Time MDOF) are facing some difficulties when fitting an FRF matrix with many columns, i.e. in cases where many input excitation locations have to be used in the modal testing. For instance, the high damping level in acoustic modal analysis requires many excitation locations to get sufficient excitation of the modes. Next to acoustic modal analysis, also structural modal analysis of trimmed vehicle bodies is a true remaining challenge and of great interest to the automotive OEMs. Moreover, when some desired constraints, e.g. identifying a reciprocal modal model or real (normal) modes in the identified modal model, are imposed it was found that the existing methods are not capable of delivering high quality models. Such models are considered as an essential requirement in several applications, e.g. updating FEM, structural modification predictions. These challenges that the user faces when using the existing modal parameter estimation methods motivates the development of the so-called MLMM estimator (Maximum Likelihood estimation of a Modal Model), where all constraints can be taken into account a prior in the formulation of the optimization problem. The developed MLMM estimator can be used also to extract modal parameters from outputs-only measurements.