Institute of Fundamental Technological Research

Jammed granular systems, also known as vacuum packed particles (VPP), have begun to compete with the well commercialized group of smart structures already widely applied in various fields of industry, mainly in civil and mechanical engineering. However, the engineering applications of VPP are far ahead of the mathematical description of the complex mechanical mechanisms observed in these unconventional structures. As their wider commercialization is hindered by this gap, in the paper the authors consider experimental investigations of granular systems, mainly focusing on the mechanical responses that take place under various temperature and strain rate conditions. To capture the nonlinear behavior of jammed granular systems, a constitutive model constituting an extension of the Johnson–Cook model was developed and is presented. green The extended and modified constitutive model for VPP proposed in the paper could be implemented in the future into a commercial Finite Element Analysis code, making it possible to carry out fast and reliable numerical simulations.

vacuum packed particles, granular jamming, smart materials, Johnson-Cook model

This paper proposes and experimentally verifies a Laplace-domain method for identification of structural modifications, which (1) unlike time-domain formulations, allows the identification to be focused on these parts of the frequency spectrum that have a high signal-to-noise ratio, and (2) unlike frequency-domain formulations, decreases the influence of numerical artifacts related to the particular choice of the FFT exponential window decay. In comparison to the time-domain approach proposed earlier, advantages of the proposed method are smaller computational cost and higher accuracy, which leads to reliable performance in more difficult identification cases. Analytical formulas for the first- and second-order sensitivity analysis are derived. The approach is based on a reduced nonparametric model, which has the form of a set of selected structural impulse responses. Such a model can be collected purely experimentally, which obviates the need for design and laborious updating of a parametric model, such as a finite element model. The approach is verified experimentally using a 26-node lab 3D truss structure and 30 identification cases of a single mass modification or two concurrent mass modifications.

structural health monitoring (SHM), nonparametric model, inverse problem, virtual distortion method (VDM), structural reanalysis, sensitivity analysis, Laplace domain

The main objective of this paper is to investigate the possibility of local structural vibration uppression via introducing initial prestressing. In order to evaluate the effectiveness of the proposed method, a two-step approach has been used. Firstly, a prestressed modal analysis has been conducted to measure the influence of the prestressing on changes of eigenfrequencies and eigenmodes. In the second step, a steady dynamic analysis has been performed to harmonic excitation to demonstrate the reduction of local amplitudes. Numerical experiments have been conducted on the model of a small rotorcraft. Our results indicate that introduction of initial prestressing may be used to affect natural structure frequancies and to lower amplitude of vibrations of the structure exposed to external extortions.

Prestressing, vibration suppression.

This paper presents a theoretical derivation and reports on a numerical verification of a model-free method for identification of added masses in truss structures. No parametric numerical model of the monitored structure is required, so that there is no need for initial model updating and fine tuning. This is a continuation and an improvement of a previous research that resulted in a time-domain identification method, which was tested to be accurate but very time-consuming. A general methodology is briefly introduced, including the inverse problem, and a numerical verification is reported. The aim of the numerical study is to test the accuracy of the proposed method and its sensitivity to various parameters (such as simulated measurement noise and decay rate of the exponential FFT window) in a numerically controlled environment. The verification uses a finite element model of the same real structure that was tested with the time-domain version of the approach. A natural further step is a lab verification based on experimental data.

In this paper, a model-free methodology for off-line identification of modifications of structural mass is proposed and verified experimentally. The methodology of the virtual distortion method is used: the modifications are modeled by the equivalent pseudo-loads that act in the related degrees of freedom of the unmodified structure; their influence on the response is computed using a convolution of the pseudo-loads with the experimentally obtained local impulse responses. As a result, experimentally measured data are directly used to model the response of the modified structure in a non-parametric way. The approach obviates the need for a parametric numerical model of the structure and for laborious initial updating of its parameters. Moreover, no topological information about the structure is required, besides potential locations of the modifications. The identification is stated as a problem of minimization of the discrepancy between the measured and the modeled responses of the modified structure. The formulation allows the adjoint variable method to be used for a quick first- and second-order sensitivity analysis, so that Hessian-based optimization algorithms can be used for fast convergence. The proposed methodology was experimentally verified using a 3D truss structure with 70 elements. Mass modifications in a single node and in two nodes were considered. Given the initially measured local impulse responses, a single sensor and single excitation were sufficient for the identification.

mass identification, structural health monitoring (SHM), virtual distortion method (VDM), model-free, non-parametric modeling, adjoint variable method

This paper present and validates experimentally a model-less methodology for off-line identification of modifications of nodal masses. The proposed approach is entirely based on experimentally measured data; hence no numerical modeling and tedious fine-tuning of the model are necessary. The influence of the added mass is modeled using virtual distortion forces and experimentally obtained system transfer matrices. The identification amounts to solving an optimization problem of minimizing the mean square distance between measured and modeled structural responses, the latter is based on previously recorded responses of the unaffected structure.

mass identification, model-less SHM, virtual distortion method (VDM), inverse dynamics

This contribution proposes a quantitative criterion for optimization of actuator placement for the Prestress–Accumulation Release (PAR) strategy of mitigation of vibrations. The PAR strategy is a semi-active control approach that relies on controlled redistribution of modal energy into high-frequency high-order modes, where it is effectively dissipated by means of the natural mechanisms of material damping. The energy transfer is achieved by a controlled temporary removal of selected structural constraints. An example is a short-time decoupling of rotational degrees of freedom in a frame node, so that the bending moments are no longer transferred between the involved beams. If it such a decoupling is performed at the maximum of the shear/bending strain energy of adjacent beams, it results in an almost instantaneous energy release into high-frequency local vibrations and quick dissipation of energy. We propose and test a quantitative criterion for placement of such actuators. The criterion is based on local modal strain energy that can be released into high-order modes. The numerical time complexity is linear with respect to the number of actuators, which facilitates quick selection of placements in large structures.

semi-active control, damping of vibrations, actuator placement, smart structures, Prestress-Accumulation Release (PAR)

This paper discusses passive and semi-active techniques of structural control by means of smart joints, and then it proposes a specific smart joints system for frame structures and tests its capability in mitigation of free vibrations. Basically, the proposed solution modifies frame beams by addition of truss-type hinges, and its effectiveness relies on the softening effect that occurs in compression due to geometric nonlinearities and which triggers the highly-damped high-frequency response modes of the structure. First, the finite element (FE) model of the specific frame structure with geometrical nonlinearities is derived, and the proposed passive joints are described and incorporated into the model. Then, their principle of operation and effectiveness is examined numerically for the first two natural modes of vibrations with various initial displacement amplitudes. An objective function is proposed to assess joints placement, based on the efficiency in mitigation of the excited vibrations.

Vibration Damping, Structure Response, Smart Structure, Structural Control

Adaptive structures, equipped with so-called structural fuses (based on fast responding piezo-devices), able to connect/disconnect instantly selected structural interface, allows effective protection against resonance induction via externally forced vibrations. The presented case study demonstrates haw forced vibrations with modifiable frequencies can be smoothly received, if structural fuses are properly activated/deactivated when the external excitation approaches the structural eigen frequencies.

Adaptive structures, forced vibrations, avoiding resonance, structural fuses

This contribution reviews the challenges in adaptive self-protection of structures. A proper semi-active control strategy can significantly increase structural ability to absorb impact-type loads and damp the resulting vibrations. Discussed systems constitute a new class of smart structures capable of a real-time identification of loads and vibration patterns, followed by a low-cost optimum absorption of the energy by structural adaptation. Given the always surging quest for safety, such systems have a great potential for practical applications (in landing gears, road barriers, space structures, etc.). Compared to passive systems, their better performance can be attributed to the paradigm of self-adaptivity, which is ubiquitous in nature, but still sparsely applied in structural engineering. Being in the early stages of development, their ultimate success depends on a concerted effort in facing a number of challenges. This contribution discusses some of the important problems, including these of a conceptual, technological, methodological and software engineering nature.

adaptive impact absorption, smart structures, semi-active control, safety engineering

The problem of dynamic response stabilization is a crucial issue in many engineering applications or structures subjected to an external source of excitation or dynamic load. At present, owing predominantly to advances in measurement technology, microprocessor control and development of smart materials it is possible to solve many of these problems. Semi-active or active damping systems, which are used to improving structure response, requires additional dampers or absorbers. Contrary, in the article we present approach of suppressing local vibration via introducing initial prestressing into the chosen element or elements of the structure. In that way it is possible to change properties of the structure and its modes of vibrations. We present the results of numerical simulations of the mechanical structure subjected to external excitations. Our results show that by introducing prestressing it is possible to significantly influence on eigenfrequances and eigenmodes. Also effectiveness of vibration amplitudes reduction can be significantly larger, at least one order of magnitude larger.

local suppresion of forced vibrations, prestressing, sensitivity analysis and prestress optimization

This paper presents a frequency-domain, nonparametric method for identification of added masses, and reports on its experimental verification. The identification is directly based on experimentally collected characteristics of the unmodified structure, so that no parametric numerical model of the monitored structure is required. Consequently, there is no need for the initial stage of model updating. This is a continuation of and an improvement over a previous research that resulted in a time-domain identification method, which was tested to be accurate but significantly time-consuming. For the experimental verification, a 4~m long 3D truss structure with 26 nodes and 70 elements is used. A total of 12 modification cases is tested: in each of 3~selected nodes, 4~additional masses are separately added and successfully identified.

This paper presents a theoretical derivation and an experimental verification of a model-free method for identification of stiffness-related damages. The proposed method requires no parametric numerical model of the monitored structure, which obviates the need for initial model updating and fine tuning. The paper introduces the general methodology, including the inverse problem, focuses it on stiffness-related damages, and reports on an experimental verification. A 4-meter-long, 70-element truss steel structure made of a commercially available system of nodes and connecting tubes is used for that purpose. Damage is simulated by an intentional replacement of a structural element.

This paper proposes a simple lab-size benchmark for testing algorithms in two identification problems related to global structural health monitoring (SHM): identification of structural modifications and identification of inelastic impacts. A 3D truss-like structure, constructed of a commercial tube/node system, is used. Structural modifications are implemented by attaching additional nodal masses or by cutting a selected element to reduce its stiffness. Inelastic impact is simulated by an impulsive excitation of an additional nodal mass. Technical specification and experimental characteristics of the unmodified structure are provided for model updating. Several modification and impact cases are experimentally tested. All the data and measurements are freely accessible in Internet. An evaluation system is proposed for assessing the solutions, based on identification accuracy, instrumentation and source lines of code. The authors encourage the readers to test their approaches on the provided data. With each solution received, the evaluations will be calculated and published online.

This paper presents and verifies experimentally a model-free methodology for off-line damage identification of truss structures. The Virtual Distortion Method (VDM) is used, which allows the approach to be based entirely on experimentally obtained non-parametric characteristics of the monitored structure, so that no parametric numerical modeling is necessary. The damage is modeled using certain damage-equivalent pseudo-loads, which are convolved with experimentally obtained local responses of the original structure to compute the response of the damaged structure. An effective sensitivity analysis is possible via the adjoint variable method.

This paper presents and experimentally validates a model-free methodology for off-line identification of modifications of structural mass. The proposed approach makes use of the Virtual Distortion Method (VDM) and is based entirely on experimentally measured data of the original unmodified structure, which is a significant advantage: no numerical modeling of the structure and tedious updating of the model are necessary. The mass modification is modeled using equivalent virtual distortion forces and experimentally obtained local impulse-responses of the unmodified structure. The identification amounts to solving an optimization problem of minimizing the mean-square distance between measured and modeled responses of the modified structure; a quick first- and second-order sensitivity analysis using the adjoint variable method is proposed. The method is validated experimentally using a 4-meter-long 70-element truss structure.

mass identification, model-free SHM, virtual distortion method (VDM), adjoint variable method

This paper proposes a new model-less method for off-line identification of a mass impacting an elastic structure. The method is aimed at the identification of both mass and its velocity, makes use of the Virtual Distortion Method (VDM) and assumes the inelastic impact case, i.e. permanent modification of structural properties. Since the proposed approach is completely based on experimentally measured data, no numerical modeling and tedious fine-tuning of the model are necessary. The impacting mass is modeled using virtual distortion forces and an experimentally obtained system transfer matrix. The identification amounts to solving an optimization problem of minimizing the mean-square distance between measured and modeled structural responses, the latter is based on previously recorded responses of the unaffected structure.

This contribution focuses on effective numerical techniques used in a nonparametric method for identification of structural mass modifications. The approach utilizes the Virtual Distortion Method (VDM), which allows experimentally measured data to be directly used in the modeling process. As a result, experimentally obtained characteristics of the involved structure are used directly, so that no parametric modeling and time-consuming fine-tuning of the parameters are necessary. On the other hand, there are significant computational costs related to the need of direct processing of the measured time series, which require effective numerical techniques. Mass identification is formulated as an optimization problem of minimizing the mean square distance between the measured and the computed structural responses, where the optimization variables are mass-related parameters. Given the testing excitation (which can be unknown but should be reproducible) and the measured response of the original undamaged structure, the corresponding response of the structural mass modifications is computed by using certain mass-equivalent pseudo loads, which are convolved with experimentally obtained local impulse responses of the unaffected structure. The methodology is validated numerically and experimentally using a 4-meter-long, 70-element truss.

mass identification, virtual distortion method (VDM), conjugate gradient least squares, FFT, nonparametric

This contribution presents the model-free approach to structural identification and monitoring, which has recently been developed in IPPT PAN [1–3]. The approach adapts the essentially nonparametric methodology of the virtual distortion method (VDM, [4]). Monitored structure is characterized in a purely experimental way, so that no parametric numerical modelling is required: the monitoring process is based directly on experimentally measured local impulse response functions. Even though, the approach can be used for identification of parametrized modifications of mass and stiffness or inelastic impacts. In comparison to other monitoring methods, it is characteristic enough to warrant the name of a model-free approach.

Most of the low-frequency methods used for global structural health monitoring (SHM, see the references in [1]) can be classified into two general groups:
1. Model-based methods, which rely on a parametric numerical model of the monitored structure. An appealing feature of these methods is the physicality of the model and identified damages; however, an accurate parametric model is often not easy to obtain.
2. Pattern recognition methods rely on a database of numerical fingerprints extracted from the experimentally measured responses. No parametric modeling is required, but at the cost of the physicality of the model. The identification rarely goes beyond damage detection or approximate localization.

The developed approach is aimed at exploiting the advantages of both groups of methods: it makes use of a nonparametric model of the monitored structure composed of experimentally measured data, but it enables full identification of parametrically expressed modifications and inelastic impacts.

This work presents and verifies experimentally a model-free methodology for off-line identification of structural damages. The Virtual Distortion Method (VDM) [1] is used, which allows the structure to be modeled locally in an essentially non-parametric way, so that no error-prone parametric modeling is necessary. The damage is modeled using damage-equivalent pseudo-loads, which are convolved with the experimentally obtained responses of the original structure to compute the response of the damaged structure. A related approach has been earlier used for model-free impact and mass identification [2,3]. An effective sensitivity analysis is possible via the adjoint variable method.