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The general problem of sizing, material and loading parameter sensitivity of non‐linear systems is presented. Both kinematic and path‐dependent material non‐linearities are considered; non‐linear sensitivity path is traced by an incremental solution strategy. The variational approach employed is quite general and can be employed for studying sensitivity of various path‐dependent highly non‐linear phenomena. Both the direct differentiation method (DDM) and adjoint system method (ASM) are discussed in the context of continuum and finite element mechanics. The merits of using the consistent tangent matrix and the necessity of accumulation of design derivatives of stresses and internal parameters are indicated. Aspects of sensitivity problems in metal forming are also discussed. A number of examples illustrate the paper.

To provide an explicit representation for wide‐sense stationary stochastic fields which can be used in stochastic finite element modelling to describe random material properties.

This method represents wide‐sense stationary stochastic fields in terms of multiple Fourier series and a vector of mutually uncorrelated random variables, which are obtained by minimizing the mean‐squared error of a characteristic equation and solving a standard algebraic eigenvalue problem. The result can be treated as a semi‐analytic solution of the Karhunen‐Loève expansion.

According to the Karhunen‐Loève theorem, a second‐order stochastic field can be decomposed into a random part and a deterministic part. Owing to the harmonic essence of wide‐sense stationary stochastic fields, the decomposition can be effectively obtained with the assistance of multiple Fourier series.

The proposed explicit representation of wide‐sense stationary stochastic fields is accurate, efficient and independent of the real shape of the random structure in consideration. Therefore, it can be readily applied in a variety of stochastic finite element formulations to describe random material properties.

This paper discloses the connection between the spectral representation theory of wide‐sense stationary stochastic fields and the Karhunen‐Loève theorem of general second‐order stochastic fields, and obtains a Fourier‐Karhunen‐Loève representation for the former stochastic fields.

To generalize the traditional 2nd order stochastic perturbation technique for input random variables and fields and to demonstrate for flow problems.

The methodology is based on an n‐th order expansion (perturbation) for input random parameters and state functions around their expected value to recover probabilistic moments of the response. A finite element formulation permits stochastic simulations on irregular meshes for practical applications.

The methodology permits approximation of expected values and covariances of quantities such as the fluid pressure and flow velocity using both symbolic and discrete FEM computations. It is applied to inviscid irrotational flow, Poiseulle flow and viscous Couette flow with randomly perturbed boundary conditions, channel height and fluid viscosity to illustrate the scheme.

The focus of the present work is on the basic concepts as a foundation for extension to engineering applications. The formulation for the viscous incompressible problem can be implemented by extending a 3D viscous primitive variable finite element code as outlined in the paper. For the case where the physical parameters are temperature dependent this will necessitate solution of highly non‐linear stochastic differential equations.

Techniques presented here provide an efficient approach for numerical analyses of heat transfer and fluid flow problems, where input design parameters and/or physical quantities may have small random fluctuations. Such an analysis provides a basis for stochastic computational reliability analysis.

The mathematical formulation and computational implementation of the generalized perturbation‐based stochastic finite element method (SFEM) is the main contribution of the paper.

This paper considers parents who misuse substances. The potential impacts of their substance misuse on their ability to parent effectively and safely (parenting capacity) are explored, as are some of the barriers many parents face when attempting to seek treatment for problematic substance misuse. The terms ‘use’ and ‘misuse’ are used interchangeably in this paper and ‘substances’ refers to alcohol, illicit drugs and overuse of prescribed medicines. It is important to make the distinction between parents whose use of substances does not constitute dependency and might be best described as ‘recreational or hazardous’. Such individuals might not seek treatment and estimates of prevalence rates of use among this cohort are difficult as they remain hidden from services. Parents who might already be in treatment services or who might be seeking treatment might be described as ‘problematic or dependent’ although presentation at services is neither necessary nor sufficient to assume that the individual's misuse of substances is problematic or indicative of a dependency. The use of substances is associated with numerous harms to the individual: psychologically, socially, interpersonally and physically, and is a risk factor towards negative parenting practices. The use of substances in itself is not an indication of neglectful or harmful parenting, as many parents who use substances have adequate parenting skills, however, it is more frequently associated as a risk rather than a protective factor when considering potential harms. Most of the research refers to mothers although we are aware that some fathers may have sole parenting responsibility for their children. Parents, in particular mothers, face many barriers when trying to access substance misuse treatment services. When they are in treatment, services often lack the skills and experiences to be able to balance managing child protection issues and engaging the parent in treatment. A full review of the issues associated with parenting and substance misuse is beyond the scope of this paper and the reader is referred to Fowler (2003), Cleaver et al (1999), Velleman and Templeton (2007) and Day and George (2005) and the British Psychological Society's Child Protection Portfolio (2007) for further discussion.

The main purpose of the paper is to propose a new approach to stochastic computational modeling of interface defects in fiber‐reinforced composites. Interface defects with random radius and total number at the fiber‐matrix interface are modeled as an interphase between original composite components with the thickness obeying all the discontinuities and material parameters of this new, fictitious material are obtained by modified spatial averaging method. Such a model is used in the stochastic finite element analysis of composites in their original configuration. Next, the probabilistic moments of global effective properties of the entire composite are estimated, thanks to the traditional Monte Carlo simulation method implementation. Numerical experiments show that introduction of the interface defects results in significant increase of randomness level of the composite displacements and the homogenized elastic characteristics. Computer programs implemented can find their applications in digital image‐based analysis and the reliability analyses for fiber‐reinforced composites.

Entrepreneurship education at universities aims to create entrepreneurial thinking and spread the culture of entrepreneurial awareness, skills and attitudes to students to stimulate their entrepreneurship intentions as graduates. This study investigates the impact of entrepreneurship education on innovative start-up intention as well as the mediating role of entrepreneurial mind-sets of university students.

Structural equation modeling (SEM) was used for analysis with (n = 204) valid questionnaires collected from university students.

The main findings show that entrepreneurial mind-sets mediate the relationship between entrepreneurship education and innovative start-up intention.

This study contributes to the body of knowledge by its application in a higher educational institution and enriches the literature with new evidence that entrepreneurship education could enhance innovative start-up intention.

The purpose of this study is to develop a stochastic finite element method (FEM) to solve the calculation precision deficiency caused by spatial variability of dam compaction quality.

The Choleski decomposition method was applied to generate constraint random field of porosity. Large-scale laboratory triaxial tests were conducted to determine the quantitative relationship between the dam compaction quality and Duncan–Chang constitutive model parameters. Based on this developed relationship, the constraint random fields of the mechanical parameters were generated. The stochastic FEM could be conducted.

When the fully random field was simulated without the restriction effect of experimental data on test pits, the spatial variabilities of both displacement and stress results were all overestimated; however, when the stochastic FEM was performed disregarding the correlation between mechanical parameters, the variabilities of vertical displacement and stress results were underestimated and variation pattern for horizontal displacement also changed. In addition, the method could produce results that are closer to the actual situation.

Although only concrete-faced rockfill dam was tested in the numerical examples, the proposed method is applicable for arbitrary types of rockfill dams.

The value of this study is that the proposed method allowed for the spatial variability of constitutive model parameters and that the applicability was confirmed by the actual project.

The present contribution deals with the sensitivity analysis and optimization of structures for path‐dependent structural response. Geometrically as well as materially non‐linear behavior with hardening and softening is taken into account. Prandtl‐Reuss‐plasticity is adopted so that not only the state variables but also their sensitivities are path‐dependent. Because of this the variational direct approach is preferred for the sensitivity analysis. For accuracy reasons the sensitivity analysis has to be consistent with the analysis method evaluating the structural response. The proposed sensitivity analysis as well as its application in structural optimization is demonstrated by several examples.

This study is centered on the identification of the most appropriate Technology Adoption (TA) model for investigating the adoption of Industry 4.0 technologies within pharmaceutical and related enterprises. The aim is to facilitate a smooth transition to advanced technologies while concurrently achieving environmental sustainability.

Selection of a suitable TA theory is carried out using a hybrid multi-criteria decision-making (MCDM) approach incorporating PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) and Fuzzy Measurement of alternatives and ranking according to Compromise solution (F-MARCOS) methods. A group of three experts is formulated for the ranking of criteria and alternatives based on those criteria.

The results indicate that out of all six TA models considered unified theory of acceptance and use of technology (UTAUT) model gets the highest utility function value, followed by the technical adoption model (TAM). Further, sensitivity analysis is conducted to confirm the validity of the MCDM model employed.

Challenging times like COVID-19 pointed out the importance of technology in the pharmaceutical and healthcare sectors. TA studies in this area can help in the identification of critical factors that can assist pharmaceutical firms in their efforts to embrace emerging technologies, enhance their outputs and increase their efficiency.

The novelty of this research lies in the fact that the utilization of a TA theory prior to its implementation has not been witnessed in existing scholarly literature. The utilization of a TA theory, specifically within the pharmaceutical industry, can assist enterprises in directing their attention toward pertinent factors when contemplating the implementation of emerging technologies and achieving sustainable development.

A general strategy is developed for adaptive finite element (FE) analysis of free vibration of elastic membranes based on the element energy projection (EEP) technique.

By linearizing the free vibration problem of elastic membranes into a series of linear equivalent problems, reliable a posteriori point-wise error estimator is constructed via EEP super-convergent technique. Hierarchical local mesh refinement is incorporated to better deal with tough problems.

Several classical examples were analyzed, confirming the effectiveness of the EEP-based error estimation and overall adaptive procedure equipped with a local mesh refinement scheme. The computational results show that the adaptively-generated meshes reasonably catch the difficulties inherent in the problems and the procedure yields both eigenvalues with required accuracy and mode functions satisfying user-preset error tolerance in maximum norm.

By reasonable linearization, the linear-problem-based EEP technique is successfully transferred to two-dimensional eigenproblems with local mesh refinement incorporated to effectively and flexibly deal with singularity problems. The corresponding adaptive strategy can produce both eigenvalues with required accuracy and mode functions satisfying user-preset error tolerance in maximum norm and thus can be expected to apply to other types of eigenproblems.