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This study aims to propose and numerically assess different ways of discretising a very weak formulation of the Poisson problem.

We use integration by parts twice to shift smoothness requirements to the test functions, thereby allowing low-regularity data and solutions.

Various conforming discretisations are presented and tested, with numerical results indicating good accuracy and stability in different types of problems.

This is one of the first articles to propose and test concrete discretisations for very weak variational formulations in primal form. The numerical results, which include a problem based on real MRI data, indicate the potential of very weak finite element methods for tackling problems with low regularity.

The purpose of this study is to numerically model the rigid pavement resting on two-parameter soil and to examine its modal parameters.

This study is carried out using a one-dimensional beam element with three rotational and three translational degrees of freedom based on the finite element method. MATLAB programming is used to perform the free vibration analysis of the rigid pavement.

Cyclic frequency and their corresponding mode shapes were determined. It has been investigated how cyclic frequency changes as a result of variations in the thickness, span length of pavement, shear modulus, modulus of subgrade, different boundary conditions and element discretization. Thickness of the pavement and span length has greater effect on the cyclic frequency. Maximum increase of 29.7% is found on increasing the thickness, whereas the cyclic frequency decreases by 63.49% on increasing span length of pavement.

The pavement's free vibration is the sole subject of the current investigation. This study limits for the preliminary design phase of rigid pavements, where a complete three-dimensional finite element analysis is unnecessary. The current approach can be extended to future research using a different method, such as finite element grilling technique, mesh-free technique on reinforced concrete pavements or jointed concrete pavements.

The finite element approach adopted in this paper involves six degrees of freedom for each node. Furthermore, to the best of the authors’ knowledge, no prior study has done seven separate parametric investigations on the modal analysis of rigid pavement resting on two-parameter soil.

Analysis of architectural space is commonly conducted by examining architectural drawings that project spatial information by means of walls and partitions. To capture the lived experience of space, which is richer than what we can see from drawings, a new method is proposed to quantify the cognitive dimension of space and re-present it as an audible format.

Using an urban vernacular house in Seoul as a case study, this research takes a syntactic approach to quantify one's changing perception through their movement from the main gate to the most private reception room. Based on Luigi Moretti's theory of hollow space, a new method is proposed to measure the level of spatial pressure exerted on a navigating body. The numerical data of spatial pressure are then converted to a sound using musical techniques of the chromatic scale and chorale textures.

Building on Moretti's abstract concept, it has been shown that a rule-based quantification of users' spatial perception is possible. In addition, unlike conventional approaches of treating architecture as a static entity, this study showed an alternative approach to represent it as a sequence of sensorial experience that can be readily converted to a sound of music.

This research developed a quantification method to measure the perception of pressure inside buildings by revisiting Luigi Moretti's theory proposed in 1952. It has been also demonstrated that the visual stimuli in space can be translated into an audible experience. This new method is applicable to a wide range of buildings including important historic architecture.

It is a well-accepted note that to enhance safety performance in a project by preventing hazards, recognizing the safety leading indicators is of paramount importance.

In this research, the relationship between safety leading indicators is determined, and their impacts on the project are assessed and visualized throughout the time of the project in a proactive manner. Construction and safety experts are first interviewed to determine the most important safety leading indicators of the construction industry, and then the relationships that may exist between them are identified. Furthermore, a system dynamics model is generated using the interviews and integrated with an add-on developed on the building information modeling (BIM) platform. Finally, the impacts of the safety leading indicators on the project are calculated based on their time of occurrence, impact time and effective radius.

The add-on generates a heat-map that visualizes the impacts of the safety leading indicators on the project through time. Moreover, to assess the effectiveness of the developed tool, a case study is conducted on a station located on a water transfer line. In order to validate the results of the tool, a survey is also conducted from the project's staff and experts in the field. Previous studies have so far focused on active safety leading indicators that may result in a particular hazard, and the importance of the effects that safety leading indicators have on another is not considered. This study considers their effects on each other in a real-time manner.

Using this tool project's stakeholders and staff can identify the hazards proactively; hence, they can make the required decisions in advance to reduce the impact of associated events. Moreover, two other potentially contributions of the presented work can be enumerated as: firstly, the findings provide a knowledge framework of active safety leading indicators and their interactions for construction safety researchers who can go on to further study safety management. Secondly, the proposed framework contributes to encouragement of time-based location-based preventive strategies on construction sites.

The use of recycled coarse aggregate in concrete structures promotes environmental sustainability; however, performance of these structures might be negatively impacted when it is used as a replacement to traditional aggregate. This paper aims to simulate recycled concrete beams strengthened with carbon fiber-reinforced polymer (CFRP), to advance the modeling and use of recycled concrete structures.

To investigate the performance of beams with recycled coarse aggregate concrete (RCAC), finite element models (FEMs) were developed to simulate 12 preloaded RCAC beams, strengthened with two CFRP strengthening schemes. Details of the modeling are provided including the material models, boundary conditions, applied loads, analysis solver, mesh analysis and computational efficiency.

Using FEM, a parametric study was carried out to assess the influence of CFRP thickness on the strengthening efficiency. The FEM provided results in good agreement with those from the experiments with differences and standard deviation not exceeding 11.1% and 3.1%, respectively. It was found that increasing the CFRP laminate thickness improved the load-carrying capacity of the strengthened beams.

The developed models simulate the preloading and loading up to failure with/without CFRP strengthening for the investigated beams. Moreover, the models were validated against the experimental results of 12 beams in terms of crack pattern as well as load, deflection and strain.

A newly developed frequency-independent lumped parameter model (LPM) is the purpose of the present paper. This new model’s direct outcome ensures high efficiency and a straightforward calculation of foundations’ vertical vibrations. A rigid circular foundation shape resting on a nonhomogeneous half-space subjected to a vertical time-harmonic excitation is considered.

A simple model representing the soil–foundation system consists of a single degree of freedom (SDOF) system incorporating a lumped mass linked to a frequency-independent spring and dashpot. Besides that, an additional fictitious mass is incorporated into the SDOF system. Several numerical methods and mathematical techniques are used to identify each SDOF’s parameter: (1) the vertical component of the static and dynamic foundation impedance function is calculated. This dynamic interaction problem is solved by using a formulation combining the boundary element method and the thin layer method, which allows the simulation of any complex nonhomogeneous half-space configuration. After, one determines the static stiffness’s expression of the circular foundation resting on a nonhomogeneous half-space. (2) The system’s parameters (dashpot coefficient and fictitious mass) are calculated at the resonance frequency; and (3) using a curve fitting technique, the general formulas of the frequency-independent dashpot coefficients and additional fictitious mass are established.

Comparisons with other results from a rigorous formulation were made to verify the developed model’s accuracy; these are exceptional cases of the more general problems that can be addressed (problems like shallow or embedded foundations of arbitrary shape, other vibration modes, etc.).

In this new LPM, the impedance functions will no longer be needed. The engineer only needs a limited number of input parameters (geometrical and mechanical characteristics of the foundation and the soil). Moreover, a simple calculator is required (i.e. we do not need any sophisticated software).

The ionization of the air surrounding the phase conductor in high-voltage transmission lines results in a phenomenon known as the Corona effect. To avoid this, Corona rings are used to dampen the electric field imposed on the insulator. The purpose of this study is to present a fast and intelligent surrogate model for determination of the electric field imposed on the surface of a 120 kV composite insulator, in presence of the Corona ring.

Usually, the structural design parameters of the Corona ring are selected through an optimization procedure combined with some numerical simulations such as finite element method (FEM). These methods are slow and computationally expensive and thus, extremely reducing the speed of optimization problems. In this paper, a novel surrogate model was proposed that could calculate the maximum electric field imposed on a ceramic insulator in a 120 kV line. The surrogate model was created based on the different scenarios of height, radius and inner radius of the Corona ring, as the inputs of the model, while the maximum electric field on the body of the insulator was considered as the output.

The proposed model was based on artificial intelligence techniques that have high accuracy and low computational time. Three methods were used here to develop the AI-based surrogate model, namely, Cascade forward neural network (CFNN), support vector regression and K-nearest neighbors regression. The results indicated that the CFNN has the highest accuracy among these methods with 99.81% R-squared and only 0.045468 root mean squared error while the testing time is less than 10 ms.

To the best of the authors’ knowledge, for the first time, a surrogate method is proposed for the prediction of the maximum electric field imposed on the high voltage insulators in the presence Corona ring which is faster than any conventional finite element method.

Previous research has analyzed the consequence of network stability; however, little is known about how partner type diversity influence network stability in R&D network. Based on knowledge-based view and social network theory, the purpose of this paper is to unravel the internal mechanisms between partner type diversity and network stability through the mediating role of knowledge recombination in R&D network.

The authors collected an unbalanced panel patent data set from information communication technology industry for the period 1994–2016. Then, the authors tested the different dimensions of partner type variety and its relevance in the R&D network and the mediating role of knowledge recombination through adopting the multiple linear regression.

Results indicate an inverted U-shaped relationship between partner type diversity (variety and relevance) and network stability, whereas knowledge recombination partially mediate these relationships.

From the perspective of R&D networks, this paper explores that there are the under-researched phenomena the antecedent of network stability through nodal attributes (i.e. partner type variety and partner type relevance). Moreover, this paper empirically examined the mediating role of knowledge recombination in the partner type diversity–network stability relationships. The novel perspective allows focal firm to recognize importance of nodal attributes, which are critical to fully excavate the potential capabilities of cooperating partners in R&D network.

This paper aims to investigate the impact of combining grain-oriented electrical steel (GOES) grades on specific iron losses and the flux density distribution within a single-phase magnetic core.

This paper presents the results of finite-element method (FEM) simulations investigating the impact of mixing two different GOES grades on losses of a single-phase magnetic core. The authors used different models: a 3D model with a highly detailed geometry including both saturation and anisotropy, as well as a simplified 2D model to save computation time. The behavior of the flux distribution in the mixed magnetic core is analyzed. Finally, the results from the numerical simulations are compared with experimental results.

The specific iron losses of a mixed magnetic core exhibit a nonlinear decrease with respect to the GOES grade with the lowest losses. Analyzing the magnetic core behavior using 2D and 3D FEM shows that the rolling direction of the GOES grades plays a critical role on the nonlinearity variation of the specific losses.

The novelty of this research lies in achieving an optimum trade-off between the manufacturing cost and the core efficiency by combining conventional and high-performance GOES grade in a single-phase magnetic core.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.