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This paper describes a practical approach to implement computational steering for problem solving environments (PSEs) by using WBCSim as an example. WBCSim is a Web based simulation system designed to increase the productivity of wood scientists conducting research on wood‐based composites manufacturing processes. WBCSim serves as a prototypical example for the design, construction, and evaluation of small‐scale PSEs.

Various changes have been made to support computational steering across the three layers – client, server, developer – comprising the WBCSim system. A detailed description of the WBCSim system architecture is presented, along with a typical scenario of computational steering usage.

The set of changes and components are: design and add a very simple steering module at the legacy simulation code level, provide a way to monitor simulation execution (alert users when it is time to steer), add an interface to access and visualize simulation results, and perhaps to compare intermediate results across multiple steering attempts. These simple changes and components have a relatively low cost in terms of increasing software complexity.

The novelty lies in designing and implementing a practical approach to enable computational steering capability for PSEs embedded with legacy simulation code.

Online privacy research has seen a focus on user behavior over the last decade, partly to understand and explain user decision-making and seeming inconsistencies regarding users' stated preferences. This article investigates the level of modeling that contemporary approaches rely on to explain said inconsistencies and whether drawn conclusions are justified by the applied modeling methodology. Additionally, it provides resources for researchers interested in using computational modeling.

The article uses data from a pre-existing literature review on the privacy paradox (N = 179 articles) to identify three characteristics of prior research: (1) the frequency of references to computational-level theories of human decision-making and perception in the literature, (2) the frequency of interpretations of human decision-making based on computational-level theories, and (3) the frequency of actual computational-level modeling implementations.

After excluding unrelated articles, 44.1 percent of investigated articles reference at least one theory that has been traditionally interpreted on a computational level. 33.1 percent of all relevant articles make statements regarding computational properties of human cognition in online privacy scenarios. Meanwhile, 5.1 percent of all relevant articles apply formalized computational-level modeling to substantiate their claims.

The findings highlight the importance of formal, computational-level modeling in online privacy research, which has so far drawn computational-level conclusions without utilizing appropriate modeling techniques. Furthermore, this article provides an overview of said modeling techniques and their benefits to researchers, as well as references for model theories and resources for practical implementation.

This paper aims to present the result of a scientometric analysis conducted using studies on high-performance computing in computational modelling. This was done with a view to showcasing the need for high-performance computers (HPC) within the architecture, engineering and construction (AEC) industry in developing countries, particularly in Africa, where the use of HPC in developing computational models (CMs) for effective problem solving is still low.

An interpretivism philosophical stance was adopted for the study which informed a scientometric review of existing studies gathered from the Scopus database. Keywords such as high-performance computing, and computational modelling were used to extract papers from the database. Visualisation of Similarities viewer (VOSviewer) was used to prepare co-occurrence maps based on the bibliographic data gathered.

Findings revealed the scarcity of research emanating from Africa in this area of study. Furthermore, past studies had placed focus on high-performance computing in the development of computational modelling and theory, parallel computing and improved visualisation, large-scale application software, computer simulations and computational mathematical modelling. Future studies can also explore areas such as cloud computing, optimisation, high-level programming language, natural science computing, computer graphics equipment and Graphics Processing Units as they relate to the AEC industry.

The study assessed a single database for the search of related studies.

The findings of this study serve as an excellent theoretical background for AEC researchers seeking to explore the use of HPC for CMs development in the quest for solving complex problems in the industry.

The purpose of this paper is to establish an intelligent framework to generate the data representatives in snapshot simulation in order to construct the online reduced-order model based on the generated data information. It could greatly reduce the computational time in snapshot simulation and accelerate the computational efficiency in the real-time computation of reduced-order modeling.

The snapshot simulation, which generates the data to construct reduced-order models (ROMs), usually is computationally demanding. In order to accelerate the snapshot generation, this paper presents a discrete element interpolaiton method (DEIM)-embedded hybrid simulation approach, in which the entire snapshot simulation is partitioned into multiple intervals of equal length. One of the three models: the full order model (FOM), local ROM, or local ROM-DEIM which represents a hierarchy of model approximations, fidelities and computational costs, will be adopted in each interval.

The outcome of the proposed snapshot simulation is an efficient ROM-DEIM applicable to various online simulations. Compared with the traditional FOM and the hybrid method without DEIM, the proposed method is able to accelerate the snapshot simulation by 54.4%–63.91% and 10.5%–27.85%, respectively. In the online simulation, ROM-DEIM only takes 4.81%–8.56% of the computational time of FOM, while preserving excellent accuracy (with relative error <1%).

1. A DEIM-embedded hybrid snapshot simulation methodology is proposed to accelerate snapshot data generation and reduced-order model (ROM)-DEIM development. 2. The simulation alternates among FOM, ROM and ROM-DEIM to adaptively generate snapshot data of salient subspace representation while minimizing computational load. 3. The DEIM-embedded hybrid snapshot approach demonstrates excellent accuracy (<1% error) and computational efficiency in both online snapshot simulation and online ROM-DEIM verification simulation.

The purpose of this paper is to propose a computational approach in order to help establish the effect of various self-piercing rivet (SPR) process and material parameters on the quality and the mechanical performance of the resulting SPR joints.

Toward that end, a sequence of three distinct computational analyses is developed. These analyses include: (a) finite-element modeling and simulations of the SPR process; (b) determination of the mechanical properties of the resulting SPR joints through the use of three-dimensional, continuum finite-element-based numerical simulations of various mechanical tests performed on the SPR joints; and (c) determination, parameterization and validation of the constitutive relations for the simplified SPR connectors, using the results obtained in (b) and the available experimental results. The availability of such connectors is mandatory in large-scale computational analyses of whole-vehicle crash or even in simulations of vehicle component manufacturing, e.g. car-body electro-coat paint-baking process. In such simulations, explicit three-dimensional representation of all SPR joints is associated with a prohibitive computational cost.

It is found that the approach developed in the present work can be used, within an engineering optimization procedure, to adjust the SPR process and material parameters (design variables) in order to obtain a desired combination of the SPR-joint mechanical properties (objective function).

To the authors’ knowledge, the present work is the first public-domain report of the comprehensive modeling and simulations including: self-piercing process; virtual mechanical testing of the SPR joints; and derivation of the constitutive relations for the SPR connector elements.

The computational model proposed in this work uses the data's of COVID-19 cases in India. From the analysis, it can be observed that the proposed immunity model decides the recovery rate of COVID −19 patients; moreover, the recovery rate does not depend on the age of the patients. These analytic models can be used by public health professionals, hospital administrators and epidemiologists for strategic decision-making to enhance health requirements based on various demographic and social factors of those affected by the pandemic. Mobile-based computational model can be used to compute the travel history of the affected people by accessing the near geographical maps of the path traveled.

In this paper, the authors developed a pediatric and geriatric person’s immunity network-based mobile computational model for COVID-19 patients. As the computational model is hard to analyze mathematically, the authors simplified the computational model as general COVID-19 infected people, the computational immunity model. The model proposed in this work used the data's of COVID-19 cases in India.

This study proposes a pediatric and geriatric people immunity network model for COVID- 19 patients. For the analysis part, the data's on COVID-19 cases in India was used. In this model, the authors have taken two sets of people (pediatric and geriatric), both are facing common symptoms such as fever, cough and myalgia. From the analysis, it was observed and also proved that the immunity level of patients decides the recovery rate of COVID-19 patients and the age of COVID-19 patients has no significant influence on the recovery rate of the patient.

COVID-19 has created a global health crisis that has had a deep impact on the way we perceive our world and our everyday lives. Not only the rate of contagion and patterns of transmission threatens our sense of agency, but the safety measures put in place to contain the spread of the virus also require social distancing. The novel model in this work focus on the Indian scenario and thereby may help Indian health organizations for future planning and organization. The factors model in this work such as age, immunity level, recovery rate can be used by machine leaning models for predicting other useful outcomes.

The purpose of this study is to propose a precise and standardized strategy for numerically simulating vehicle aerodynamics.

Error sources in computational fluid dynamics were analyzed. Additionally, controllable experiential and discretization errors, which significantly influence the calculated results, are expounded upon. Considering the airflow mechanism around a vehicle, the computational efficiency and accuracy of each solution strategy were compared and analyzed through numerous computational cases. Finally, the most suitable numerical strategy, including the turbulence model, simplified vehicle model, calculation domain, boundary conditions, grids and discretization scheme, was identified. Two simplified vehicle models were introduced, and relevant wind tunnel tests were performed to validate the selected strategy.

Errors in vehicle computational aerodynamics mainly stem from the unreasonable simplification of the vehicle model, calculation domain, definite solution conditions, grid strategy and discretization schemes. Using the proposed standardized numerical strategy, the simulated steady and transient aerodynamic characteristics agreed well with the experimental results.

Building upon the modified Low-Reynolds Number k-e model and Scale Adaptive Simulation model, to the best of the authors’ knowledge, a precise and standardized numerical simulation strategy for vehicle aerodynamics is proposed for the first time, which can be integrated into vehicle research and design.

A large‐strain/high‐deformation rate model for clay‐free sand recently proposed and validated in our work [1,2], has been extended to sand containing relatively small (< 15vol.%) of clay and having various levels of saturation with water. The model includes an equation of state which represents the material response under hydrostatic pressure, a strength model which captures material behavior under elastic‐plastic conditions and a failure model which defines conditions and laws for the initiation and evolution of damage/failure in the material. The model was validated by comparing the computational results associated with detonation of a landmine in clayey sand (at different levels of saturation with water) with their computational counterparts.

Elasto‐plastic models based on critical state formulations have been successful in describing many of the most important features of the mechanical behaviour of soils. This review paper deals with the applications of this class of models to the numerical analysis of geotechnical problems. After a brief overview of the development of the models, the basic critical state formulation is presented together with the main modifications which have actually been used in computational applications. The problems associated with the numerical implementation of this type of models are then discussed. Finally, a summary of reported computational applications and some specific examples of analyses of geotechnical problems using critical state models are presented.

Computational modeling brings unique and critical contributions to behavioral and social research. Computational modeling can transform logic models into dynamic models and helps formalize complex theory construction. Computational modeling opens new vistas in data designs and data analysis. Computational models allow us to explore systems not in dynamic equilibrium, to understand the implications of different initialization conditions, to examine complex system synergies through process decomposition, and to provide policy-related tools such as counterfactual simulations.