The Experts below are selected from a list of 48 Experts worldwide ranked by ideXlab platform

Ricarose Roque - One of the best experts on this subject based on the ideXlab platform.

  • the Simulation Cycle combining games Simulations engineering and science using starlogo tng
    E-learning, 2009
    Co-Authors: Eric Klopfer, Hal Scheintaub, Wendy Huang, Daniel Wendel, Ricarose Roque
    Abstract:

    StarLogo The Next Generation (TNG) enables secondary school students and teachers to model decentralized systems through agent-based programming. TNG's inclusion of a three- dimensional graphical environment provides the capacity to create games and Simulation models with a first-person perspective. The authors theorize that student learning of complex systems and Simulations can be motivated and improved by transforming Simulation models of complex systems phenomena (specifically this study examines systems including epidemics and Newtonian motion) into games. Through this transformation students interact with the model in new ways and increase their learning of both specific content knowledge and general processes such as inquiry, problem solving and creative thinking. During this study several methods for connecting the Simulations to game dynamics were tried, ranging from student-created games, to altering existing games, to students playing pre- made games. This article presents the results of research data from two years of curriculum development and piloting in northern Massachusetts science classrooms to demonstrate the successes and challenges of integrating Simulations and games. This article also explores the results of these interventions in terms of ease of implementation, student motivation and student learning. Two teams are building models of virtual worlds. They each need to consider the relevant aspects of the world that they want to represent, focusing on what is important for their purposes, and what is superfluous. They also need to consider how they will provide appropriate inputs into their system and understand the output of their models, including whether the feedback that the models provide is clear. Each team needs to cleverly devise algorithms that appropriately represent the actions and behaviors of the inhabitants of their virtual world, and investigate the outcomes that they observe. In many ways the actions of these two teams are indistinguishable. However, as the products progress, the differences become more pronounced - one team is developing and studying a Simulation of warming seas designed to help scientists save endangered species; the other is building a jet ski racing game designed to entertain. Both of these products require good initial models of fluid dynamics, tide flow, buoyancy, and many other physical parameters as a starting place. They may both incorporate information about how weather impacts the oceans - either to make the Simulation more accurate or to make the game more exciting. The Simulation requires important biological parameters to describe the ocean inhabitants, whereas the game requires important physical information to simulate the behavior of the jet ski under different ocean conditions. Of course there are distinct differences between the way the game and the Simulation are developed and studied. These differences allow the Simulation to be more predictive, and the game to be more engaging. But perhaps they are more similar than distinct. It is this connection between the design and building of games and Simulations that motivates the research and development of our Simulations, Systems and Computational Literacy (SSCL) curriculum and the corresponding tool, StarLogo The Next Generation (TNG). Simulations are an

Hayub Song - One of the best experts on this subject based on the ideXlab platform.

  • robot based facade spatial assembly optimization
    Journal of building engineering, 2021
    Co-Authors: Ahmed Khairadeen Ali, One Jae Lee, Hayub Song
    Abstract:

    Abstract Robotic involvement in construction is still in its initial stages compared to other industries. Conventionally, the facade panel picking position is done manually by trial and error. The designer chooses a place to pick up a facade piece within reach of the robot arm, and then simulates the entire pick and place process in a digital model before applying to the assembly on the construction job site. After that the designer might detect errors, collisions, or singularities, which require the designer to modify the position of picking by changing the location or orientation of the module, thus repeating the Simulation Cycle until they reach a satisfactory result with no errors or collisions. This work is usually considered monotonous, inefficient, and time consuming. Therefore, this research proposes an optimization process implemented in design stage of construction project via static performance criteria in order to automatically search for the best picking location within the reach of the robot arm. The goal is to automate the process of robot location finding and solve the limitations of modular robot assembly Simulation processes in order to allow for effective execution during the robotic construction implementation. The proposed approach, called iFobot, consists of three modules: Facade Generative Modeling (iFobot-D), Robot Position Optimization (iFobot-B), and Culminating Feedback to BIM (iFobot-L). Specifically, the scope of the paper is limited to the robot arm and facade picking and placing location finding processes. This research allows initial assessment of the possible assembly process as regards the dimensions of modules and hence the overall dimensions of the system, which subsequently influences assembly implementation in the construction job site. A set of generative algorithms were developed using commercially developed visual programming language that automatically populate facade modules on the building envelope, find the robot and facade assembly locations with their quantity take-off, and integrate the module with the BIM environment. A case study has been developed to validate and test the proposed system. The results prove that the system generates optimized locations for the robot arm workstations with the lowest possible collision and reachability rate while addressing robot operation time reduction, thus reducing risks encountered during facade assembly and increasing productivity. Moreover, the iFobot is predicted to influence decision making during the facade assembly process on a physical construction job site.

Eric Klopfer - One of the best experts on this subject based on the ideXlab platform.

  • the Simulation Cycle combining games Simulations engineering and science using starlogo tng
    E-learning, 2009
    Co-Authors: Eric Klopfer, Hal Scheintaub, Wendy Huang, Daniel Wendel, Ricarose Roque
    Abstract:

    StarLogo The Next Generation (TNG) enables secondary school students and teachers to model decentralized systems through agent-based programming. TNG's inclusion of a three- dimensional graphical environment provides the capacity to create games and Simulation models with a first-person perspective. The authors theorize that student learning of complex systems and Simulations can be motivated and improved by transforming Simulation models of complex systems phenomena (specifically this study examines systems including epidemics and Newtonian motion) into games. Through this transformation students interact with the model in new ways and increase their learning of both specific content knowledge and general processes such as inquiry, problem solving and creative thinking. During this study several methods for connecting the Simulations to game dynamics were tried, ranging from student-created games, to altering existing games, to students playing pre- made games. This article presents the results of research data from two years of curriculum development and piloting in northern Massachusetts science classrooms to demonstrate the successes and challenges of integrating Simulations and games. This article also explores the results of these interventions in terms of ease of implementation, student motivation and student learning. Two teams are building models of virtual worlds. They each need to consider the relevant aspects of the world that they want to represent, focusing on what is important for their purposes, and what is superfluous. They also need to consider how they will provide appropriate inputs into their system and understand the output of their models, including whether the feedback that the models provide is clear. Each team needs to cleverly devise algorithms that appropriately represent the actions and behaviors of the inhabitants of their virtual world, and investigate the outcomes that they observe. In many ways the actions of these two teams are indistinguishable. However, as the products progress, the differences become more pronounced - one team is developing and studying a Simulation of warming seas designed to help scientists save endangered species; the other is building a jet ski racing game designed to entertain. Both of these products require good initial models of fluid dynamics, tide flow, buoyancy, and many other physical parameters as a starting place. They may both incorporate information about how weather impacts the oceans - either to make the Simulation more accurate or to make the game more exciting. The Simulation requires important biological parameters to describe the ocean inhabitants, whereas the game requires important physical information to simulate the behavior of the jet ski under different ocean conditions. Of course there are distinct differences between the way the game and the Simulation are developed and studied. These differences allow the Simulation to be more predictive, and the game to be more engaging. But perhaps they are more similar than distinct. It is this connection between the design and building of games and Simulations that motivates the research and development of our Simulations, Systems and Computational Literacy (SSCL) curriculum and the corresponding tool, StarLogo The Next Generation (TNG). Simulations are an

Eric Ramat - One of the best experts on this subject based on the ideXlab platform.

  • the virtual laboratory environment an operational framework for multi modelling Simulation and analysis of complex dynamical systems
    Simulation Modelling Practice and Theory, 2009
    Co-Authors: Gauthier Quesnel, Raphael Duboz, Eric Ramat
    Abstract:

    The cross-disciplinary activity of modelling and Simulation is the core of the scientific activities addressing the complexity of nature. In this context, we need reliable computational environments to integrate heterogeneous representations coming from different scientific fields. Therefore, such environments must be able to integrate heterogeneous formalisms in the same model and assist the modeller for the design and implementation of models, the definition of the experimental frames and the analysis of Simulation results. The aim of this article is to introduce a tool supporting all these features, the Virtual Laboratory Environment (VLE). VLE is a software and an API which supports multi-modelling, Simulation and analysis. It addresses the reliability issue by using recent developments in the theory of modelling and Simulation proposed by Zeigler. We present VLE in the context of the modelling and Simulation Cycle and show the effectiveness of the tool with a multimodel of fireman fighting a fire spread.

Abdul Jalal, Rifqi Irzuan - One of the best experts on this subject based on the ideXlab platform.

  • Vehicle Fuel Economy Improvement through Vehicle Optimization in 1-D Simulation Cycle towards Energy Efficient Vehicle (EEV)
    'Penerbit UTHM', 2020
    Co-Authors: Zainal Abidin, Shaiful Fadzil, Khalid Amir, Shafai@shafie, Siti Nor Zulaikha, Zahari Izzarief, Abdul Jalal, Rifqi Irzuan
    Abstract:

    The high average of fuel consumption in vehicle for ASEAN countries compared to global average has led to the establishment of Energy Efficient Vehicle (EEV) by National Automotive Policy (NAP) 2014. PROTON Saga 1.3L 4-speed automatic transmission (4AT) with 6.80 L/100km fuel consumption, it is crucial to reduce the fuel consumption in order to fulfil the NAP 14 target which is 6.0 L/100km so that it stays competitive in the market and also to support the ASEAN emission legislation. The objectives of this research are to design and develop a 1-Dimensional 4-AT vehicle model for fuel economy and performance analysis as well as to evaluate and optimize vehicle model to achieve the product target and legislation requirements. The PROTON Saga 1.3L 4-AT vehicle model which is a B-Segment passenger vehicle will be developed using 1-Dimensional Simulation software. The correlation between the base vehicle model and actual vehicle model is 0.14% for fuel consumption and 2.22% for 0-100km/h, since the value is less than 4%, the vehicle model can be concluded as valid and authentic. All the data and engine maps used in this research are provided by PROTON Engineering Department to support the accuracy of findings. For each parameter considered in this research, the optimization was performed in Simulation where it begins from the current vehicle engine configuration and then applying each parameter at each step until the anticipated configuration of vehicle has achieved. The parameters involved in this research are vehicle weight, aerodynamic, rolling resistance, final gear ratio, and idle speed. Stop start system was used as an advanced alternative way to mitigate the fuel consumption since it is cost consuming. The fuel consumption for an optimized model is 6.01 L/100km with 0.17% difference with the real target which is 6.0 L/100km. The current vehicle model fuel consumption is 6.80 L/100km, thus, it has been successfully reduced to 6.01 L/100km which is equivalent to 11.62% without implementing stop start system and 25.03% with the implementation of stop start system. It seems that the beneficial to examine various possible solution concepts, and to establish understanding on the effectiveness and synergies between powertrain technologies and vehicle design in reducing the overall fuel consumption ad emission