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This paper aims to present an evolutionary algorithm (EA) to accelerate the convergence for the radiative transfer equation (RTE) numerical solution using high-order and high-resolution schemes by the relaxation coefficients optimization.

The objective function minimizes the residual value difference between iterations in each control volume until its difference is lower than the convergence criterion. The EA approach is evaluated in two configurations, a two-dimensional cavity with scattering media and absorbing media.

Experimental results show the capacity to obtain the numerical solution for both cases on all interpolation schemes tested by the EA approach. The EA approach reduces CPU time for the RTE numerical solution using SUPERBEE, SWEBY and MUSCL schemes until 97% and 135% in scattering and absorbing media cases, respectively. The relaxation coefficients optimized every two numerical solution iterations achieve a significant reduction of the CPU time compared to the deferred correction procedure with fixed relaxation coefficients.

The proposed EA approach for the RTE numerical solution effectively reduces the CPU time compared to the DC procedure with fixed relaxation coefficients.

The flux vector splitting (FVS) schemes are known for their higher resistance to shock instabilities and carbuncle phenomena in high-speed flow computations, which are generally accompanied by relatively large numerical diffusion. However, it is desirable to control the numerical diffusion of FVS schemes inside the boundary layer for improved accuracy in viscous flow computations. This study aims to develop a new methodology for controlling the numerical diffusion of FVS schemes for viscous flow computations with the help of a recently developed boundary layer sensor.

The governing equations are solved using a cell-centered finite volume approach and Euler time integration. The gradients in the viscous fluxes are evaluated by applying the Green’s theorem. For the inviscid fluxes, a new approach is introduced, where the original upwind formulation of an FVS scheme is first cast into an equivalent central discretization along with a numerical diffusion term. Subsequently, the numerical diffusion is scaled down by using a novel scaling function that operates based on a boundary layer sensor. The effectiveness of the approach is demonstrated by applying the same on van Leer’s FVS and AUSM schemes. The resulting schemes are named as Diffusion-Regulated van Leer’s FVS-Viscous (DRvLFV) and Diffusion-Regulated AUSM-Viscous (DRAUSMV) schemes.

The numerical tests show that the DRvLFV scheme shows significant improvement over its parent scheme in resolving the skin friction and wall heat flux profiles. The DRAUSMV scheme is also found marginally more accurate than its parent scheme. However, stability requirements limit the scaling down of only the numerical diffusion term corresponding to the acoustic part of the AUSM scheme.

To the best of the authors’ knowledge, this is the first successful attempt to regulate the numerical diffusion of FVS schemes inside boundary layers by applying a novel scaling function to their artificial viscosity forms. The new methodology can reduce the erroneous smearing of boundary layers by FVS schemes in high-speed flow applications.

To compute an optimal control of non‐linear reaction diffusion equations that are modelling inhibitor problems in the brain.

A new numerical approach that combines a spectral method in time and the Adomian decomposition method in space. The coupling of these two methods is used to solve an optimal control problem in cancer research.

The main conclusion is that the numerical approach we have developed leads to a new way for solving such problems.

Focused research on computing control optimal in non‐linear diffusion reaction equations. The main idea that is developed lies in the approximation of the control space in view of the spectral expansion in the Legendre basis.

Through this work we are convinced that one way to derive efficient numerical optimal control is to associate the Legendre expansion in time and Runge Kutta approximation. We expect to obtain general results from optimal control associated with non‐linear parabolic problem in higher dimension.

Coupling of methods provides a numerical solution of an optical control problem in Cancer research.

Job analysis is the common basis for designing a training course or programme, preparing performance tests, writing position (job) descriptions, identifying performance appraisal criteria, and job restructuring. Its other applications in human resource development include career counselling and wage and salary administration. Job analysis answers the questions of what tasks, performed in what manner, make up a job. Outputs of this analytical study include: (a) a list of the job tasks; (b) details of how each task is performed; (c) statements describing the responsibility, job knowledge, mental application, and dexterity, as well as accuracy required; and (d) a list of the equipment, materials, and supplies used to perform the job. Various techniques for conducting a job analysis have been used. Each has its advantages and disadvantages. As a result, different techniques or combinations of techniques are appropriate to different situations. The combined on‐site observation and individual interview techniques are recommended for industrial, trade, craft, clerical, and technical jobs because they generate the most thorough and probably the most valid information. A job analysis schedule is used to report the job information obtained through observations and individual interviews. The schedule provides a framework of 12 items in which to arrange and describe important job analysis information. These 12 items are organised into four sections. Section one consists of items one through four. These items identify the job within the establishment in which it occurs. The second section presents item five, the work performed. It provides a thorough and complete description of the tasks of the job. The Work Performed section describes what the job incumbent does, how it is done, and why it is done. Section three presents items six through nine. These are the requirements placed on the job incumbent for successful performance. It is a detailed interpretation of the basic minimum (a) responsibility, (b) job knowledge, (c) mental application, and (d) dexterity and accuracy required of the job incumbent. The fourth section includes three items which provide background information on the job. These items are: (a) equipment, materials and supplies; (b) definitions of terms; and (c) general comments. Appendix A is a glossary of terms associated with job analysis. It is provided to facilitate more exacting communication. A job analysis schedule for a complex and a relatively simple job are included in Appendices B and C. These examples illustrate how important job analysis information is arranged and described. Appendix D provides a list of action verbs which are helpful when describing the manipulative tasks of a job.

Numerical simulation of polymer injection processes has become increasingly common in mould design. In industry, such a task is accomplished mainly by using commercial packages. Owing to the complexities inherent of this class of problems, most commercial codes attempt to combine realistic rheological descriptions with simplified numerical models. In spite of the apparent success, such approaches are not able to capture important aspects of the flow topology. The present work aims to describe a more elaborate mathematical model based on finite volumes which is able to provide both accurate solutions and further insights on the physics of the polymer flow.

The mathematical model comprises the momentum and energy equations and a Poisson equation for pressure to impose the incompressibility constraint. The governing equations are discretized using the finite volume method based on central, second‐order accurate formulas for both convection and diffusion terms. Artificial dissipation terms are added externally in order to control the odd‐even decoupling problem.

The numerical model was conceived within the framework of a generalized Newtonian formulation. The capability of the numerical scheme is illustrated by simulations using three distinct constitutive relations to approach the non‐Newtonian behaviour of the polymer melt: isothermal power‐law, modified Arrhenius power‐law and cross models.

This paper extends the computational strategies previously developed to Newtonian fluids to account for more complex constitutive relations. The velocity and temperature coupled solution for polymer melts using only second‐order accurate formulas constitute also a relevant contribution.

The purpose of the study is to obtain explicit formulas to determine the stability of periodic solutions to the new system and study the extent of the stability of those periodic solutions and the direction of bifurcated periodic solutions. More than that, the authors did a numerical simulation to confirm the results that the authors obtained and presented through numerical analysis are the periodic and stable solutions and when the system returns again to the state of out of control.

The authors studied local bifurcation and verified its occurrence after choosing the delay as a parameter of control in Zhou 2019’s dynamical system with delayed feedback control. The authors investigated the normal form theory and the center manifold theorem.

The occurrence of local Hopf bifurcations at the Zhou's system is verified. By using the normal form theory and the center manifold theorem, the authors obtain the explicit formulas for determining the stability and direction of bifurcated periodic solutions. The theoretical results obtained and the corresponding numerical simulations showed that the chaos phenomenon in the Zhou's system can be controlled using a method of time-delay auto-synchronization.

As the delay increases further, the numerical simulations show that the periodic solution disappears, and the chaos attractor appears again. The obtained results can also be applied to the control and anti-control of chaos phenomena of system (1). There are still abundant and complex dynamical behaviors, and the topological structure of the new system should be completely and thoroughly investigated and exploited.

The purpose of this paper is to develop a novel unstructured simulation approach for injection molding processes described by the Hele‐Shaw model.

The scheme involves dual dynamic meshes with active and inactive cells determined from an initial background pointset. The quasi‐static pressure solution in each timestep for this evolving unstructured mesh system is approximated using a control volume finite element method formulation coupled to a corresponding modified volume of fluid method. The flow is considered to be isothermal and non‐Newtonian.

Supporting numerical tests and performance studies for polystyrene described by Carreau, Cross, Ellis and Power‐law fluid models are conducted. Results for the present method are shown to be comparable to those from other methods for both Newtonian fluid and polystyrene fluid injected in different mold geometries.

With respect to the methodology, the background pointset infers a mesh that is dynamically reconstructed here, and there are a number of efficiency issues and improvements that would be relevant to industrial applications. For instance, one can use the pointset to construct special bases and invoke a so‐called “meshless” scheme using the basis. This would require some interesting strategies to deal with the dynamic point enrichment of the moving front that could benefit from the present front treatment strategy. There are also issues related to mass conservation and fill‐time errors that might be addressed by introducing suitable projections. The general question of “rate of convergence” of these schemes requires analysis. Numerical results here suggest first‐order accuracy and are consistent with the approximations made, but theoretical results are not available yet for these methods.

This novel unstructured simulation approach involves dual meshes with active and inactive cells determined from an initial background pointset: local active dual patches are constructed “on‐the‐fly” for each “active point” to form a dynamic virtual mesh of active elements that evolves with the moving interface.

The paper aims to design a process to mechanize traditional chasing and repoussé which is the art of creating an artistic pattern on a sheet metal by making high and low points through utilization of hammer and chisel. In scientific literature, it is a kind of incremental sheet metal forming.

In the designed process, a magnetic actuator is used as a hammer which converts electric energy into kinetic reciprocal impact energy, and hammering sequence is completely controlled via the designed software. The sheet is bound not to move easily. Then, a hammering mechanism is connected to the numerical control machine. As the magnetic hammer is moved gradually along the defined path, the sheet is chased gradually by controlling the consecutive impacts. Different methods of test sheet entanglement are also discussed to reduce noise and undesired deformations of sheet, and indents are also clarified.

The designed mechanism enables the user to form desired art patterns faster with more precision via the automated process. The hammering sequence is controlled via computer successfully. The designed magnetic actuator could be commercialized easily. Experiments show that the pitch under sheet is the best. Typical art patterns are chased successfully.

In incremental sheet metal punching, there was no control on hammering sequence before. In this process, the designed magnetic hammer is quite controllable. Also, it is easily attached to the computerized numerical control (CNC) and is suitable for commercial use. Furthermore, the stuff under sheet was not taken into consideration before.

The optimal control of the steady‐state temperature distribution in radiating panels using control heat sources is considered. The problem has important applications in the thermal control of space structures. A mathematical model leads to an elliptic nonlinear optimal control problem. A numerical optimal control method, based on finite element (FE) discretization and sequential quadratic programming (SQP), is employed. Results are presented for some specific examples.

The purpose of this paper is to identify key factors that influence the decision to adopt computerized numerical control (CNC) and direct numerical control (DNC) machines, material working lasers and robots (specific advanced manufacturing technologies – AMT) using the theory of planned behavior (TPB) as the underlying framework.

Firms that had recently adopted a shop floor manufacturing technology were surveyed. Structural equation modeling was used to analyze the 123 responses.

The TPB explained a substantial amount of variance in behavioral intentions to adopt an AMT. As proposed, attitude towards adoption and subjective norms significantly influence a decision maker. However, perceived behavioral control did not have a significant impact on intentions. The TPB was shown to be an effective predictor of technology adoption in a specific context.

Single respondents were used – future research might include multiple respondents. Though sufficient statistical power was realized, there was a relatively low response rate – future research may pre‐screen potential respondents to ensure eligibility.

Primary implications include: adopters may be willing to tolerate a difficult adoption process in order to realize significant competitive benefits; suppliers of AMT may want to develop greater customer knowledge to influence adoption decisions; and champions of AMT adoption may want to proactively influence the opinions of other key stakeholders.

The research context was controlled by focusing on a specific type of AMT. Further, actual technology adoption decisions were investigated. Most applications of the TPB assume that the “intentions” to “behavior” relationship holds.