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The purpose of this paper is to describe an innovative approach to overcoming a common dilemma in designing negotiation simulations – that of situating a simulation in a real-life or fictitious context. This binary choice, which the authors call the negotiation designer’s dilemma, has profound implications for the types of learning activities and outcomes that can be integrated into the overall learning experience. As a way of overcoming the trade-offs inherent in this dilemma, the authors developed what they term hybrid simulations, which blend elements of fact and fiction in its contextual design in a particular way.

The authors were part of a negotiation simulation design team that used Design Thinking to understand the negotiation designer’s dilemma and to prototype and test a corresponding solution.

This paper demonstrates the benefits, potential applications and the how-to of hybrid simulations within the context of two such simulations the authors have designed at two different Swiss business schools. This paper concludes by discussing the potential and limitations for the application of hybrid simulations, as well as areas of potential further development.

The concept of a hybrid negotiation is a novel design trick that can be used in a variety of negotiation simulation contexts.

Gas insulated systems, such as gas insulated lines (GIL), use insulating gas, mostly sulfur hexalfluoride (SF₆), to enable a higher dielectric strength compared to e.g. air. However, under high voltage direct current conditions, charge accumulation and electric field stress may occur, which may lead to partial discharge or system failure. Therefore, numerical simulations are used to design the system and determine the electric field and charge distribution. Although the gas conduction shows a more complex current–voltage characteristic compared to solid insulation, the electric conductivity of the SF₆ gas is set as constant in most works. The purpose of this study is to investigate different approaches to address the conduction in the gas properly for numerical simulations.

In this work, two approaches are investigated to address the conduction in the insulating gas and are compared to each other. One method is an ion-drift-diffusion model, where the conduction in the gas is described by the ion motion in the SF₆ gas. However, this method is computationally expensive. Alternatively, a less complex approach is an electro-thermal model with the application of an electric conductivity model for the SF₆ gas. Measurements show that the electric conductivity in the SF₆ gas has a nonlinear dependency on temperature, electric field and gas pressure. From these measurements, an electric conductivity model was developed. Both methods are compared by simulation results, where different parameters and conditions are considered, to investigate the potential of the electric conductivity model as a computationally less expensive alternative.

The simulation results of both simulation approaches show similar results, proving the electric conductivity for the SF₆ gas as a valid alternative. Using the electro-thermal model approach with the application of the electric conductivity model enables a solution time up to six times faster compared to the ion-drift-diffusion model. The application of the model allows to examine the influence of different parameters such as temperature and gas pressure on the electric field distribution in the GIL, whereas the ion-drift-diffusion model enables to investigate the distribution of homo- and heteropolar charges in the insulation gas.

This work presents numerical simulation models for high voltage direct current GIL, where the conduction in the SF₆ gas is described more precisely compared to a definition of a constant electric conductivity value for the insulation gas. The electric conductivity model for the SF₆ gas allows for consideration of the current–voltage characteristics of the gas, is computationally less expensive compared to an ion-drift diffusion model and needs considerably less solution time.

The purpose of this systematic review was to explore the benefits and challenges in the implementation of simulation-based education (SBE) in the classroom and clinical settings in sub-Saharan Africa. The objectives of this systematic review were to identify the benefits of utilising SBE in the classroom and clinical practice in sub-Saharan Africa and to assess the challenges in the implementation of SBE in the classroom and clinical practice in sub-Saharan Africa.

Five databases were searched for existing English literature (Medline, CINAHL and Science Direct), including grey literature on the subject. Out of 26 eligible studies conducted in sub-Saharan Africa between 2014 and 2021, six studies that used mixed-methods design were included. Hawker et al.’s framework was used to assess the quality of the studies. Quantitative data were presented using descriptive and inferential statistics in the form of means and standard deviations while qualitative data were analysed and presented thematically.

Quantitative findings showed that participants rated SBE highly in terms of teaching (93.2%), learning (91.4%) and skill acquisition (88.6%). SBE improved the clinical skill competency from 30% at baseline to 75% at the end. On the other hand, qualitative findings yielded themes namely: improved confidence and competence; knowledge acquisition and critical thinking; motivation and supervision; independent, self-paced learning; simulation equipment and work schedules; and planning and delivery of simulation activity. Pedagogical skills, competence and confidence are some of the elements that determine the feasibility of implementing SBE in the classroom and clinical settings.

SBE could help to bridge the gap between theory and practice and improve the quality of care provided by nurses. Simulation-based training is effective in improving the clinical skills of midwives and increasing their confidence in providing care. However, SBE trainees require motivation and close supervision in classroom settings if simulation is to be successfully implemented in sub-Saharan Africa. Furthermore, careful planning of scenarios, students briefing and reading of content prior to implementation facilitate effective simulation.

While there may be a lack of literature on the use of SBE for training nurses and midwives in the developing world, there is growing evidence that it can be an effective way to improve clinical skills and quality of care. However, there are also significant challenges to implementing simulation-based training in resource-limited settings, and more research is needed to understand how best to address these challenges. This study fills this gap in the literature.

With hybrid simulation techniques getting popular for systems improvement in multiple fields, this study aims to provide insight on the use of hybrid simulation to assess the effect of lean manufacturing (LM) techniques on manufacturing facilities and the transition of a mass production (MP) facility to incorporating LM techniques.

In this paper, the authors apply a hybrid simulation approach to improve an educational automotive assembly line and provide guidelines for implementing different LM techniques. Specifically, the authors describe the design, development, verification and validation of a hybrid discrete-event and agent-based simulation model of a LEGO® car assembly line to analyze, improve and assess the system’s performance. The simulation approach examines the base model (MP) and an alternative scenario (just-in-time [JIT] with Heijunka).

The hybrid simulation approach effectively models the facility. The alternative simulation scenario (implementing JIT and Heijunka LM techniques) improved all examined performance metrics. In more detail, the system’s lead time was reduced by 47.37%, the throughput increased by 5.99% and the work-in-progress for workstations decreased by up to 56.73%.

This novel hybrid simulation approach provides insight and can be potentially extrapolated to model other manufacturing facilities and evaluate transition scenarios from MP to LM.

This paper aims to research the tribological and dynamic characteristics of aeroengine hybrid ceramic bearings through wear experiments and simulation analysis.

First, the authors carried out wear experiments on Si₃N₄–GCr15 and GCr15–GCr15 friction pairs through the ball-disc wear test rig to explore the tribological properties of their materials. Second, using ANSYS/LS-DYNA simulation software, the dynamic simulation analysis of hybrid bearings was carried out under certain working conditions, and the dynamic contact stress of all-steel bearings of the same size was simulated and compared. Finally, the change of the maximum contact stress of the main bearing under the change of load and rotation speed was studied.

The results show that the Si₃N₄–GCr15 pair has better tribological performance. At the same time, under the conditions of high speed and heavy load, the simulation analysis shows that the contact stress between the ceramic ball and the raceway of the ring is smaller than the steel ball. That is, hybrid bearings have better transient mechanical properties than all-steel bearings. With the speed increasing to 12,000 r/min, the maximum stress point will shift in the inner and outer rings.

In this study, the tribological and transient mechanical properties of Si₃N₄ material were comprehensively analyzed through wear experiments and dynamic simulation analysis, which provided a reference for the design of hybrid bearings for next-generation aeroengines.

Assess the realistic impacts of implementing an Radio Frequency Identification (RFID)/Internet of Things (IoT) uniforms’ distribution system for managing medical personnel’s scrubs in operating rooms. The authors use a hybrid simulation framework to address the following objectives and challenges: a) reduce and control operating rooms’ level of inventory; b) stabilize scrubs’ demand and c) improve infection control and prevention of cross-contamination (through scrubs over manipulation and hoarding).

The authors adopt a Design Science approach. This methodological approach is used to design, develop, create and evaluate information technology “artifacts” (e.g. constructs, models, methods and instantiations) intended to solve organizational problems and make research contributions (Peffers et al., 2007). More specifically, the authors follow the Design Science Research Methodology process model which includes six steps: problem identification and motivation, definition of the objectives for a solution, design and development, demonstration, evaluation, and communication.

To assess the realistic impacts of implementing an RFID-IoT uniforms’ distribution system for managing medical personnel’s scrubs in operating rooms, the authors adopted a design science approach and initiated the research by documenting the business case and reviewed the existing literature to build a comparative analysis of existing uniforms’ distribution systems. The authors used a hybrid simulation model to assess the impact of three business cases: present mode of operation, implementing smart shelves or the smart distributors. The authors show that smart dispensers allow a greater control on scrubs’ utilization while eliminating the cross-contamination of the medical personnel.

Through this research study, the authors provide hospitals’ managers a scientific support for uniforms’ (scrubs) distribution process improvement. The authors use a hybrid simulation model to compare innovative solutions for uniforms’ distribution systems in the form of “smart cabinets” supported by Radio Frequency Identification (RFID)/Internet of Things (IoT) technologies and choose the most appropriate design for the hospital to meet two main challenges: a) inefficiency of uniform replenishment-distribution system and b) noncompliancy with infection control regulations caused by the distribution system.

From a methodological perspective, this paper addresses concerns from researchers calling quantitative research methods and using case-based research strategy to address IoT issues and assess the system in practice. From a broader point of view, this work confirms the predominant interest of RFID-IoT research work in the arena of supply chain management and logistics as the technology is used for tracking purpose and for monitoring applications. It is also one response to the research community suggesting that “hospitals should evaluate the medical effectiveness of the new technologies as well as the cost before adoption”.

The purpose of this paper is to investigate the research landscape of LSS 4.0 papers published in two well-known repositories, Scopus and Web of Science (WoS), in terms of publication trends, article distribution by author, journal, affiliations and country, and article clustering based on keywords, authors and countries. In addition, a literature review was carried out to build a conceptual framework of integrated Lean Six Sigma and Industry 4.0 (LSS 4.0) that encompasses operational, sustainability and human factors or ergonomics aspects.

The literature review of integrated Lean Six Sigma and I4.0 publications published in Scopus and WoS databases in the current decade was conducted for the present study. This study categorizes LSS, I4.0 and related research articles based on publication patterns, journals, authors and affiliations, country and continental-wise distribution and clustering the articles based on keywords and authors from the Scopus and WoS databases from 2011 to 2022 using the search strings “Lean”, “Six Sigma”, “Lean Six Sigma” and “Industry 4.0” in the Title, Abstract and Keywords using Biblioshiny, VOS viewer and Microsoft Excel.

In the recent three years, from 2020 to 2022, LSS 4.0 has been substantially increasing and is seen as an emerging and trending area. This research identifies the most influential authors, most relevant affiliations, most prolific countries and most productive journals and clusters based on keywords, authors and countries. Further, a conceptual framework was developed that includes the impact of operational, sustainability and ergonomic or human factors in LSS 4.0.

This article assists in comprehending the trends and patterns of LSS 4.0. Further, the conceptual framework helps professionals and researchers understand the significance and impact of integrating LSS and Industry 4.0 in the aspects of human factors/ergonomic, sustainability and operations. Also, the research induce professionals to incorporate all these factors while designing and implementing LSS 4.0 in their organization.

This conceptual framework and bibliometric analysis would aid in identifying potential areas of research and providing future directions in the domain of LSS 4.0. It will be beneficial for academicians, professionals and researchers who are planning to apply and integrate techniques of LSS and technologies of I4.0 in their organizations and research.

Heat exchangers (HEs) which provide heat transfer and transfer energy through direct or indirect contact between fluids have an essential role in many processes as a part of various industries from pharmaceutical production to electronic devices. Using nanofluid as working fluid and integrating different types of turbulators could be used to upgrade the thermal effectiveness of HEs. Recently, to obtain more increment in thermal effectiveness, hybrid nanofluids are used that are prepared by mixing two or more various nanoparticles. The purpose of this experimental and numerical study is investigating different scenarios for improving the effectiveness of a concentric U-tube type HE.

In the numerical section of this study, different turbulator modifications, including circular and quarter circular rings, were modeled to determine the effect of adding turbulator on thermal performance. In addition, Al₂O₃/water and SiO₂/water single and Al₂O₃–SiO₂/water hybrid nanofluids were experimentally tested in an unmodified concentric U-tube HE in two different modes, including counter flow and parallel flow. Al₂O₃–SiO₂/water hybrid nanofluid was prepared at 2% (wt./wt.) particle ratio and compared with Al₂O₃/water and SiO₂/water single type nanofluids at same particle ratios and with distilled water.

Numerical modeling findings exhibited that integrating turbulators to the concentric tube type HE caused to raise in the effectiveness by improving heat transfer area. Also, experimental results indicated that using both hybrid and single type nanofluids notably upgraded the thermal performance of the concentric U-tube HE. Integrating turbulators cannot be an effective alternative in a concentric U-tube type HE with lower diameter because of raise in pressure drop. Numerically achieved findings exhibited that using quarter circular turbulators decreased pressure drop in comparison with circular turbulators. According to the experimental outcomes, using hybrid Al₂O₃–SiO₂/water nanofluid leads to obtain more thermal performance in comparison with single type nanofluids. The highest increment in overall heat transfer coefficient of HE by using Al₂O₃–SiO₂/water nanofluid achieved as 58.97% experimentally.

The overall outcomes of the current research exhibited the positive impacts of using hybrid nanofluid and integrating turbulators. In this empirical and numerical survey, numerical simulations were performed to specify the impact of applying different turbulators and hybrid nanofluid on the flow and thermal characteristics in a concentric U-tube HE. The achieved outcomes exhibited that using hybrid nanofluid can notably increase the thermal performance with negligible pressure drop in comparison with two different turbulator modifications.

This paper aims to employ a multivariate nonlinear regression analysis to establish a predictive model for the final fracture area, while accounting for the impact of individual parameters.

This analysis is based on the numerical simulation data obtained, using the hybrid finite element–discrete element (FE–DE) method. The forecasting model was compared with the numerical results and the accuracy of the model was evaluated by the root mean square (RMS) and the RMS error, the mean absolute error and the mean absolute percentage error.

The multivariate nonlinear regression model can accurately predict the nonlinear relationships between injection rate, leakoff coefficient, elastic modulus, permeability, Poisson’s ratio, pore pressure and final fracture area. The regression equations obtained from the Newton iteration of the least squares method are strong in terms of the fit to the six sensitive parameters, and the model follow essentially the same trend with the numerical simulation data, with no systematic divergence detected. Least absolutely deviation has a significantly weaker performance than the least squares method. The percentage contribution of sensitive parameters to the final fracture area is available from the simulation results and forecast model. Injection rate, leakoff coefficient, permeability, elastic modulus, pore pressure and Poisson’s ratio contribute 43.4%, −19.4%, 24.8%, −19.2%, −21.3% and 10.1% to the final fracture area, respectively, as they increased gradually. In summary, (1) the fluid injection rate has the greatest influence on the final fracture area. (2)The multivariate nonlinear regression equation was optimally obtained after 59 iterations of the least squares-based Newton method and 27 derivative evaluations, with a decidability coefficient R2 = 0.711 representing the model reliability and the regression equations fit the four parameters of leakoff coefficient, permeability, elastic modulus and pore pressure very satisfactorily. The models follow essentially the identical trend with the numerical simulation data and there is no systematic divergence. The least absolute deviation has a significantly weaker fit than the least squares method. (3)The nonlinear forecasting model of physical parameters of hydraulic fracturing established in this paper can be applied as a standard for optimizing the fracturing strategy and predicting the fracturing efficiency in situ field and numerical simulation. Its effectiveness can be trained and optimized by experimental and simulation data, and taking into account more basic data and establishing regression equations, containing more fracturing parameters will be the further research interests.

The nonlinear forecasting model of physical parameters of hydraulic fracturing established in this paper can be applied as a standard for optimizing the fracturing strategy and predicting the fracturing efficiency in situ field and numerical simulation. Its effectiveness can be trained and optimized by experimental and simulation data, and taking into account more basic data and establishing regression equations, containing more fracturing parameters will be the further research interests.

The calculation of electromagnetic fields can involve many degrees of freedom (DOFs) to achieve accurate results. The DOFs are directly related to the computational effort of the simulation. The effort is decreased by using the proper generalized decomposition (PGD) and proper orthogonalized decomposition (POD). The purpose of this study is to combine the advantages of both methods. Therefore, a hybrid enrichment strategy is proposed and applied to different electromagnetic formulations.

The POD is an a-priori method, which exploits the solution space by decomposing reference solutions of the field problem. The disadvantage of this method is given by the unknown number of solutions necessary to reconstruct an accurate field representation. The PGD is an a-priori approach, which does not rely on reference solutions, but require much more computational effort than the POD. A hybrid enrichment strategy is proposed, based on building a small POD model and using it as a starting point of the PGD enrichment process.

The hybrid enrichment process is able to accurately approximate the reference system with a smaller computational effort compared to POD and PGD models. The hybrid enrichment process can be combined with the magneto-dynamic T-Ω formulation and the magnetic vector potential formulation to solve eddy current or non-linear problems.

The PGD enrichment process is improved by exploiting a POD. A linear eddy current problem and a non-linear electrical machine simulation are analyzed in terms of accuracy and computational effort. Further the PGD-AV formulation is derived and compared to the PGD-T-Ω reduced order model.