Search results

The purpose of this paper is to develop robust metamodels, which allow propagating parametric uncertainties, in the presence of localized nonlinearities, with reduced cost and without significant loss of accuracy.

The proposed metamodels combine the generalized polynomial chaos expansion (gPCE) for the uncertainty propagation and reduced order models (ROMs). Based on the computation of deterministic responses, the gPCE requires prohibitive computational time for large-size finite element models, large number of uncertain parameters and presence of nonlinearities. To overcome this issue, a first metamodel is created by combining the gPCE and a ROM based on the enrichment of the truncated Ritz basis using static residuals taking into account the stochastic and nonlinear effects. The extension to the Craig–Bampton approach leads to a second metamodel.

Implementing the metamodels to approximate the time responses of a frame and a coupled micro-beams structure containing localized nonlinearities and stochastic parameters permits to significantly reduce computation cost with acceptable loss of accuracy, with respect to the reference Latin Hypercube Sampling method.

The proposed combination of the gPCE and the ROMs leads to a computationally efficient and accurate tool for robust design in the presence of parametric uncertainties and localized nonlinearities.

The durability of concrete structures, especially built-in corrosive environments, starts to deteriorate after 20–30 years, even though they have been designed for more than 60 years of service life. The durability of concrete depends on its resistance against a corrosive environment. Inorganic Polymer concrete, or geopolymer concrete, has been emerging as a new engineering material with the potential to form an alternative to conventional concrete for the construction industry. The purpose of this paper is to conduct the investigation on corrosion of the geopolymer materials prepared using GGBS blended with low calcium fly ash in different percentages and sodium hydroxide, sodium silicate as activators and cured in ambient conditions (25±5°C).

GGBS was replaced by fly ash at different levels from 0 to 50 percent in a constant concentration of 12M. The main parameters of this study are the evaluation of strength characteristics of geopolymer concrete and resistance against corrosion by conducting accelerated corrosion test (Florida method).

From the test results it is observed that the strength of the geopolymer concrete with GGBS in ambient curing performs well compared to geopolymer concrete with GGBS blended with fly ash. The GPCE sample (40 percent replacement of fly ash to GGBS) shows better results and the resistance against corrosion was good, compared to all other mixes.

The outcomes of this investigation will be useful for the researchers and the construction industry.

This paper results that optimum percentage of fly ash should be blended with GGBS against the corrosion attack. This investigation indicates that GGBS without the combination of fly ash can be utilized in a normal environment. These findings will definitely be useful for the ready-mix concrete manufacturers and the construction Industry.

Disposal of industrial wastes causes pollution to the environment. Industrial wastes are utilized for the production of geopolymer concrete, which is the alternative material for the construction industry.

From the observation of the previous literature, till now there was no investigation on geopolymer concrete for corrosion under ambient curing conditions, as such this investigation could be considered as the new investigation.

To present the models with many model parameters by polynomial chaos expansion (PCE), and improve the accuracy, this paper aims to present dimension-adaptive algorithm-based PCE technique and verify the feasibility of the proposed method through taking solid rocket motor ignition under low temperature as an example.

The main approaches of this work are as follows: presenting a two-step dimension-adaptive algorithm; through computing the PCE coefficients using dimension-adaptive algorithm, improving the accuracy of PCE surrogate model obtained; and applying the proposed method to uncertainty quantification (UQ) of solid rocket motor ignition under low temperature to verify the feasibility of the proposed method.

The result indicates that by means of comparing with some conventional non-invasive method, the proposed method is able to raise the computational accuracy significantly on condition of meeting the efficiency requirement.

This paper proposes an approach in which the optimal non-uniform grid that can avoid the issue of overfitting or underfitting is obtained.

The purpose of this paper is to develop a new formulation using spectral approach, which can predict the wave behavior to uncertain parameters in mid and high frequencies.

The work presented is based on a hybridization of a spectral method called the “wave finite element (WFE)” method and a non-intrusive probabilistic approach called the “polynomial chaos expansion (PCE).” The WFE formulation for coupled structures is detailed in this paper. The direct connection with the conventional finite element method allows to identify the diffusion relation for a straight waveguide containing a mechanical or geometric discontinuity. Knowing that the uncertainties play a fundamental role in mid and high frequencies, the PCE is applied to identify uncertainty propagation in periodic structures with periodic uncertain parameters. The approach proposed allows the evaluation of the dispersion of kinematic and energetic parameters.

The authors have found that even though this approach was originally designed to deal with uncertainty propagation in structures it can be competitive with its low time consumption. The Latin Hypercube Sampling (LHS) is also employed to minimize CPU time.

The approach proposed is quite new and very simple to apply to any periodic structures containing variabilities in its mechanical parameters. The Stochastic Wave Finite Element can predict the dynamic behavior from wave sensitivity of any uncertain media. The approach presented is validated for two different cases: coupled waveguides with and without section modes. The presented results are verified vs Monte Carlo simulations.

The purpose of this paper is to propose a generic approach that prevents a specific class of code injection attacks (CIAs) in a novel way.

To defend against CIAs this approach involves detecting attacks by using location‐specific signatures to validate code statements. The signatures are unique identifiers that represent specific characteristics of a statement's execution. The key property that differentiates the scheme presented in this paper is that these characteristics do not depend entirely on the code statement, but also take into account elements from its execution context.

The approach was applied successfully to defend against attacks targeting structured query language (SQL), XML Path Language and JavaScript with positive results.

Despite many countermeasures that have been proposed the number of CIAs has been increasing. Malicious users seem to find new ways to introduce compromised embedded executable code to applications by using a variety of languages and techniques. Hence, a generic approach that defends against such attacks would be a useful countermeasure. This approach can defend attacks that involve both domain‐specific languages (e.g. SQL) and general purpose languages (e.g. JavaScript) and can be used both against client‐side and server‐side attacks.

The definition of modeling languages is a key‐prerequisite for model‐driven engineering. In this respect, Domain‐Specific Modeling Languages (DSMLs) defined from scratch in terms of metamodels and the extension of Unified Modeling Language (UML) by profiles are the proposed options. For interoperability reasons, however, the need arises to bridge modeling languages originally defined as DSMLs to UML. Therefore, the paper aims to propose a semi‐automatic approach for bridging DSMLs and UML by employing model‐driven techniques.

The paper discusses problems of the ad hoc integration of DSMLs and UML and from this discussion a systematic and semi‐automatic integration approach consisting of two phases is derived. In the first phase, the correspondences between the modeling concepts of the DSML and UML are defined manually. In the second phase, these correspondences are used for automatically producing UML profiles to represent the domain‐specific modeling concepts in UML and model transformations for transforming DSML models to UML models and vice versa. The paper presents the ideas within a case study for bridging ComputerAssociate's DSML of the AllFusion Gen CASE tool with IBM's Rational Software Modeler for UML.

The ad hoc definition of UML profiles and model transformations for achieving interoperability is typically a tedious and error‐prone task. By employing a semi‐automatic approach one gains several advantages. First, the integrator only has to deal with the correspondences between the DSML and UML on a conceptual level. Second, all repetitive integration tasks are automated by using model transformations. Third, well‐defined guidelines support the systematic and comprehensible integration.

The paper focuses on the integrating direction DSMLs to UML, but not on how to derive a DSML defined in terms of a metamodel from a UML profile.

Although, DSMLs defined as metamodels and UML profiles are frequently applied in practice, only few attempts have been made to provide interoperability between these two worlds. The contribution of this paper is to integrate the so far competing worlds of DSMLs and UML by proposing a semi‐automatic approach, which allows exchanging models between these two worlds without loss of information.