Integrated Simulation Tool Research Articles

Passive Strategies for thermal comfort in Amazonian Cities: The Case of Tena's Waterfront"

This study explores the application of passive strategies focused on reducing urban heat islands, with special attention to improving pedestrian thermal comfort in Amazonian cities. Based on climatic data such as temperature, humidity, solar radiation, and wind speed, the impact of urban morphology on public space, particularly on the Tena River waterfront, is analyzed. Using the Grasshopper and Ladybug simulation tools, two scenarios were compared: one current, with 2-3 story buildings, and one proposed, which includes buildings up to 6 stories integrated with native vegetation. The results demonstrate that the proposed scenario not only increases shading but also significantly contributes to the reduction of temperatures, confirming the viability of these strategies to enhance sustainable urban design and improve the quality of life in Amazonian environments. The evaluation of the results highlights aspects to improve in urban development and emphasizes the importance of integrating simulation tools to design urban proposals and open spaces, guaranteeing a comfort zone for the user, encouraging pedestrian routes and therefore increasing social relations in nearby public spaces.

Optimizing Outdoor Thermal Comfort for Educational Buildings: Case Study in the City of Riyadh

In hot, arid climates, educational buildings often face the challenge of limited outdoor space usage. This research, through comprehensive simulation, aims to propose practical solutions to enhance outdoor thermal comfort, particularly during school break times and student dismissal periods, thereby fostering more comfortable and functional outdoor school environments. That will happen through achieving the main objective of the study, which is evaluating the suggested passive strategies. Riyadh was selected as the case study, and four representative schools were analyzed through simulation and optimization processes to identify key areas for improvement. The research leveraged simulation tools such as Ladybug and Grasshopper in Rhino, highlighting the practicality and impact of this approach. Simulations were performed to assess the existing outdoor thermal conditions using the universal thermal climate index (UTCI) and to pinpoint regions with elevated thermal discomfort. Passive design interventions, such as shading devices and vegetation, were explored and optimized using the Galapagos in Grasshopper. This methodology supports the originality of this research in its integration of simulation tools, such as Ladybug and Grasshopper, with optimization techniques using the Galapagos plugin, specifically applied to the unique site-specific context of educational outdoor environments in a hot, dry climate in Riyadh. Additionally, insights for urban planners and architects demonstrate the possibility of integrating passive design principles to improve the usability and sustainability of outdoor spaces. The findings indicated that fewer apertures in shade devices combined with greater tree canopies might double the effectivity in lowering UTCI values, thereby enhancing thermal comfort, especially during peak summer months.

SIMULATION-DRIVEN STRATEGIES FOR ENHANCING WATER TREATMENT PROCESSES IN CHEMICAL ENGINEERING: ADDRESSING ENVIRONMENTAL CHALLENGES

Water treatment processes in chemical engineering play a critical role in addressing environmental challenges and ensuring the sustainability of water resources. This paper examines simulation-driven strategies aimed at enhancing water treatment processes within the domain of chemical engineering. By leveraging advanced simulation techniques and methodologies, engineers can optimize the design, operation, and performance of water treatment systems, thereby mitigating environmental impacts and improving overall efficiency. The review highlights the importance of addressing environmental challenges through innovative approaches in water treatment processes. It underscores the role of simulation-driven strategies in chemical engineering to achieve sustainable solutions for water management. Through a comprehensive review of simulation techniques and case studies, this paper elucidates how simulation-driven approaches can enhance the effectiveness and sustainability of water treatment processes. Furthermore, the review emphasizes the interdisciplinary nature of this research, bridging chemical engineering principles with environmental science and technology. By integrating simulation tools with knowledge of water chemistry, fluid dynamics, and process engineering, engineers can develop robust strategies for optimizing water treatment processes while minimizing environmental footprints. Key topics covered include the application of computational fluid dynamics (CFD), process simulation software, and advanced modeling techniques in the analysis and design of water treatment systems. Case studies illustrating the successful implementation of simulation-driven strategies in various water treatment applications are presented to provide practical insights and demonstrate the potential benefits. Overall, this paper underscores the pivotal role of simulation-driven strategies in advancing water treatment processes in chemical engineering. It advocates for the adoption of innovative approaches to address environmental challenges and promote sustainability in water management practices within the oil and gas industry and other sectors reliant on chemical engineering processes.
 Keywords: Water treatment, Environmental Challenges, Chemical Engineering, Processes, Simulation Driven Strategies.

A Deep Reinforcement Learning Strategy for Surrounding Vehicles-Based Lane-Keeping Control.

As autonomous vehicles (AVs) are advancing to higher levels of autonomy and performance, the associated technologies are becoming increasingly diverse. Lane-keeping systems (LKS), corresponding to a key functionality of AVs, considerably enhance driver convenience. With drivers increasingly relying on autonomous driving technologies, the importance of safety features, such as fail-safe mechanisms in the event of sensor failures, has gained prominence. Therefore, this paper proposes a reinforcement learning (RL) control method for lane-keeping, which uses surrounding object information derived through LiDAR sensors instead of camera sensors for LKS. This approach uses surrounding vehicle and object information as observations for the RL framework to maintain the vehicle's current lane. The learning environment is established by integrating simulation tools, such as IPG CarMaker, which incorporates vehicle dynamics, and MATLAB Simulink for data analysis and RL model creation. To further validate the applicability of the LiDAR sensor data in real-world settings, Gaussian noise is introduced in the virtual simulation environment to mimic sensor noise in actual operational conditions.

PlatoonSAFE: An Integrated Simulation Tool for Evaluating Platoon Safety

PlatoonSAFE: An Integrated Simulation Tool for Evaluating Platoon Safety

Development of a multi-physic platform OLYMPE for magnet fusion design: Progresses update and applications

In the framework of tokamak design studies, the magnet system dimensioning stands as a crucial point, magnets being strong drivers for reactor performances. In this aim superconducting magnets design path to manufacture and integration should undergo several stages of development, including the detailed analysis for defined operation cases. Those studies are linked to several physic domains (electromagnetics, mechanics, thermohydraulics, thermal) that all show interdependances between each other. In this objective, the platform OLYMPE was developed at CEA, aiming at addressing those complex multi-physic problems in an integrated simulation tool, expected to improve the efficiency of the design workflow involving macroscopic and detailed analyses.The different OLYMPE submodules will be described and their dedicated simulation domain explained, together with the logic that led to the choice of specific modules interconnection. In fact several combinations of those modules are built in coupled mode so to ensure converging design loops. Their major role is to assess the refinement of magnet design at detailed scale in the objective to increase magnet design accuracy. Namely illustrating examples will be given with following loops:- TF system design coupled with thermohydraulics: it ensures the compliance of TF design with temperature margin criterion.- TF system design coupled with electromagnetics: it ensures the compliance of TF design with topologically-induced magnetic field map.- Overall TF design coupled with thermohydraulics and cryogenics: it ensures the optimization of TF design and its operation conditions with overall system merits (e.g. cost factor).- TF system design coupled with mechanics: it ensures the compliance of TF design with local stress criterion.The outcomes and methodological merits of these loops will be illustrated by applications on DEMO configurations, and performances cross-checks or comparisons with simpler models will also be provided to quantify the accuracy enhancement.Furthermore the management of the overall input database and the GUI interface will be presented in the aim of improving tool operability.Finally discussions on this emerging OLYMPE tool qualities will also be exposed, including calculation performances merits and further development perspectives.

Detailed transient assessment of a small-scale concentrated solar power plant based on the organic Rankine cycle

• New procedures for modeling the components of solar-ORC power plant are proposed. • A routine for optimizing the turbine geometry and evaluating its performance is used. • The power plant results are obtained by coupling the accurate components models. • A power plant continuously supplying electricity to remote communities is designed. • The low ODP and GWP refrigerant R1233zd(E) provided the best performance. Motivated by environmental issues and the needs of communities that live far from the electricity grid, this work presents an innovative methodology for modeling a small-scale concentrated solar power plant based on the organic Rankine cycle. An integrated simulation tool, which consists of accurate computational routines of the energy storage tank, parabolic trough collector, plate heat exchanger, finned air-cooled condenser, and inward-flow radial turbine, is developed. The components are modeled according to distributed models and the mean line method for the turbine in homemade codes to account for local property changes. The transient power plant performance is assessed by employing solar irradiation data of three locations that present mean direct normal irradiation rates of 6306, 4712, and 3220 Wh/m 2 .day. The following working fluids were considered: a low GWP and ODP refrigerant (R1233zd(E)), a natural one (R600a), and a high GWP fluid that is currently employed for such applications (R245fa). The smallest configuration that led to annual uninterrupted power production is a 565-m 2 collector and a 90-m 3 storage tank. The R1233zd(E) refrigerant presented the best overall performance by providing about 2% and 30% higher turbine power output, 3% and 29% higher turbine efficiency, and 4% and 36% higher ORC first-law efficiency than R245fa and R600a, respectively. The designed solar power plant generated 48.396 MWh/year of electricity and 80.621 MWh/year of cogeneration energy with R1233zd(E), which is enough to provide electricity and sanitary hot water to about 33 and 64 houses, respectively.

Virtual laboratory to conduct slip test of synchronous machine

The educational system is presently undergoing a substantial change to improve the teaching-learning process of all engineering domains. This includes the utilization of user-friendly simulation tools as part of the laboratory for an enhanced practical experience on a virtual platform. Owing to the advantages of virtual experimentation, engineering laboratories are now preferably integrated with suitable simulation tools. This paper deals with the integration of simulation tools with undergraduate courses of electrical machinery. For this purpose, a simulation model was developed to conduct the slip test on a three phase synchronous machine on a virtual platform using MATLAB or Simulink for the determination of direct axis reactance Xd and quadrature axis reactance Xq . From the test results, a close relationship between the calculated value of synchronous reactance and rated parameters of the machine is observed, showing the acceptability and suitability of conducted test for the integration of virtual platform with laboratory session. Concept of virtual laboratory may be extended to undergraduate course of electrical machinery during teaching-learning process.

Мультиагентная модель многономенклатурного мелкосерийного производства

Production planning is a key aspect when optimizing production activities. Simulation is one of the most effective methods available for assessing production problems. The principles of adaptive planning consist of making day-to-day operational decisions at the shop floor, predicting equipment availability, assessing performance, and eliminating bottlenecks. Existing research to eliminate bottlenecks has focused on analyzing data from the physical shop, or vice versa, only on the use of simulated data. Convergence between real and simulated data allows, on the one hand, to obtain more information to predict the availability of each workplace, on the other hand, it allows performance assessment for replanning using a simulation model. Aim. Development of optimization tools for production planning using simulation approaches. Materials and methods. This article presents a multi-agent simulation model for each workplace in the workshop, examines the workload of the workshop, and evaluates the productivity of workplaces. Optimization is proposed for optimal utilization of production facilities. As an example illustrating the efficiency and advantage of the proposed model, we took the production process of electronic equipment in the assembly shop. Results. A planning problem and an approach to optimization are formulated. A multi-agent model of multinomenclature small-scale production has been developed. The model provides for the integration of simulation tools with operational planning systems at the data level. Conclusion. The model proposed in the study allows small-scale production to plan the number of jobs and identify bottlenecks in production. The use of a combination of simulation and planning tools ensures enterprise resource management, taking into account dynamic changes in the system.

Improving the Performance of Controllers for Wind Turbines on Semi-Submersible Offshore Platforms: Fuzzy Supervisor Control

The use of sea wind energy is restricted by the limited availability of suitable sites in shallow waters. To overcome this challenge, wind turbines located on offshore semi-submersible platforms appear as a valuable option, as they also allow the exploitation of other resources like wave energy or aquaculture. Nevertheless, the literature addressing this kind of design is scarce, and the interactions of the wind turbine and the platform movements increase the complexity of the control system with respect to the wind turbines with fixed foundations. Within this context, fuzzy control is a promising alternative to deal with these issues. However, while fuzzy controllers can be an alternative to substitute conventional PI control, the latter is a well-known, robust choice for operators. In this sense, fuzzy controllers can be designed to work in collaboration with PI controllers to ease their adoption. To this end, this paper addresses those gaps in the literature by presenting a methodology, its application to enhance controllers for large-scale wind turbines in semi-submersible offshore platforms and the results attained. The methodology is based on the implementation of an integrated simulation tool, together with the definition of three indexes that describe the performance of the control system in the overall platform behaviour regarding key aspects of its exploitation. Using it, an Anti-Wind-Up algorithm was designed to improve the behaviour of the conventional controller and is presented and evaluated along a fuzzy supervisor controller. In this kind of configuration, the fuzzy controller modifies the values of the PI controller. Finally, a comparison of the performance using the reference PI and the improved PI, in both cases together with a fuzzy supervisor controller modifying their values, is presented and discussed, contributing to extend the state of the art of controllers for large-scale wind turbines on offshore semi-submersible platforms.

Design and validation of microfluidic parameters of a microfluidic chip using fluid dynamics

The internal fluidic parameters of microfluidic channels must be analyzed to solve fundamental microfluidic problems, including microscale transport problems involving thermal analysis, chemical reactivity, velocity, pressure drop, etc., for developing good-quality chemical and biological products. Therefore, the characterization and optimization of the interaction of chemical and biological solutions through microfluidic channels are vital for fluid flow design and engineering for quality assurance in microfluidic platforms. As the internal structures and kinetics of microfluidic channels are becoming increasingly complex, experiments involving optimal fluidic and transport designs are challenging to perform with high accuracy. However, highly integrated simulation tools can guide researchers without specialized computational fluid backgrounds to design numerical prototypes of highly integrated devices. In this study, a microfluidic chip with two inlet wells and one outlet well was fabricated from polydimethylsiloxane following which simulations were performed using an ANSYS Fluent tool influenced by computational fluid dynamics at a nearly identical scale. The pressure drop and velocity profiles of the interaction of two pH buffer solutions (pH 4 and 10) through the designed microfluidic chip were qualitatively estimated from experimental data analysis and validated with the simulation results obtained from the CFD-influenced ANSYS Fluent tool.

Optimization of water management plans for CSP plants through simulation of water consumption and cost of treatment based on operational data

Considering the importance of water in local communities and the development of Concentrated Solar Thermal Power (CSP) projects in arid regions, water footprint analysis and finding water-saving solutions towards optimized use of raw water resources in CSP plants are essential. Within this study, we present an integrated simulation tool for a comprehensive simulation of CSP plants including the water and wastewater streams, treatment units, and the cost of treatment. The models are compared to a set of measured water consumption data from a commercial CSP plant. Furthermore, strategies to reduce raw water consumption are identified and then investigated through the detailed simulation of alternative water management plans. The results show that with optimized solutions, raw water consumption can be reduced by 14% while the cost of electricity remains the same or is even slightly reduced.

A Simulation Tool for Evaluating Video Streaming Architectures in Vehicular Network Scenarios

An integrated simulation tool called Video Delivery Simulation Framework over Vehicular Networks (VDSF-VN) is presented. This framework is intended to allow users to conduct experiments related to video transmission in vehicular networks by means of simulation. Research on this topic requires the use of many independent tools, such as traffic and network simulators, intermediate frameworks, video encoders and decoders, converters, platform-dependent scripting languages, data visualisation packages and spreadsheets, and some other tasks are performed manually. The lack of tools necessary to carry out all these tasks in an integrated and efficient way formed the motivation for the development of the VDSF-VN framework. It is managed via two user-friendly applications, GatcomSUMO and GatcomVideo, which allow all the necessary tasks to be accomplished. The first is primarily used to build the network scenario and set up the traffic flows, whereas the second involves the delivery process of the whole video, encoding/decoding video, running simulations, and processing all the experimental results to automatically provide the requested figures, tables and reports. This multiplatform framework is intended to fill the existing gap in this field, and has been successfully used in several experimental tests of vehicular networks.

Materials Design Through Batch Bayesian Optimization with Multisource Information Fusion

Integrated computational materials engineering (ICME) calls for the integration of simulation tools and experiments to accelerate the development of materials. ICME approaches tend to be computationally costly, and recently, Bayesian optimization (BO) has been proposed as a way to make ICME more resource efficient. Conventional BO, however, is sequential (i.e., one-at-a-time) in nature, which makes it very time-consuming when the evaluation of a materials design choice is costly. While conventional high-throughput approaches enable the synthesis and characterization (or simulation) of materials in a parallel manner, they tend to be “open loop” and are unable to provide recommendations of what to try next once the parallel experiment/simulation has been carried out and analyzed. Here, we address this problem by introducing a batch BO framework that enables the exploration of the material’s design space in a parallel fashion. We augment this approach by incorporating information fusion frameworks capable of integrating multiple information sources. Demonstrating the proposed approach in the computational design of dual-phase steel, we show that batch BO can result in a significant reduction in the time and resources needed to carry out the design task. The proposed approach has wider applicability, well beyond the ICME example used to demonstrate it.

Evaluating the Environmental Benefits of Median Bus Lanes: Microscopic Simulation Approach

Median bus lanes are an important element of bus rapid transit (BRT) systems, and can improve traffic operations by separating bus traffic from the traffic in general-purpose lanes. Thus, the operation of BRT systems with dedicated bus lanes is expected to reduce energy consumption and produce positive environmental impacts to a substantial degree. This study attempts to quantify the impacts for a corridor in Seoul, South Korea where frequent bus services are provided, using an integrated simulation tool composed of a microscopic traffic model and a vehicle emissions simulator. This approach has rarely been applied for evaluating the environmental benefits of BRT systems. Given a high volume of bus traffic, the simulation results reveal that corridor energy consumption can be reduced by 18.5% and emissions can be reduced by 19.3–31.4%, depending on the pollutant (CO, CO2, PM10, PM2.5, NOx). Vehicles in general-purpose lanes contribute 99.0% of the emissions reductions, with the remaining 1.0% contributed by transit buses. Considering that vehicles in general-purpose lanes represent 94% of corridor traffic, and provide 99.0% of the emission reduction contribution, the simulations suggest that median bus lanes benefit not only the bus operations, but also significantly improve the traffic flow in the general-purpose lanes, contributing to the overall corridor emissions reductions.

Impact of foundation modelling in offshore wind turbines: Comparison between simulations and field data

The design of Offshore Wind Turbines (OWTs) relies on integrated simulation tools capable of predicting the system dynamic characteristics and the coupled loads and responses. Despite all efforts to develop accurate integrated models, these often fail to reproduce the measured natural frequencies, partly due to the modelling of the foundation. Several foundation models and calibration approaches have been proposed and compared with small or large scale field tests, where only the soil and the foundation are included. However, there is a lack of more integral validation where the interaction between the foundation and the structure is taken into account. The paper investigates the impact of the foundation model and calibration approach on the simulated response of a monopile-based OWT installed in the North Sea by comparing simulations and full-scale field data. The OWT structure and the environmental actions are implemented in the aero-servo-hydro-elastic code 3DFloat. Two foundation models and two calibration approaches are evaluated. The results indicate that, with a conceptually correct foundation model and a realistic calibration, it is possible to match the measured natural frequency and predict accurate fatigue loads. More accurate predicted loads will reduce uncertainties in the estimated fatigue lifetime and therefore reduce risk in the design.

Parallel Closed-Loop Connected Vehicle Simulator for Large-Scale Transportation Network Management: Challenges, Issues, and Solution Approaches

The augmented scale and complexity of urban transportation networks have significantly increased the execution time and resource requirements of vehicular network simulations, exceeding the capabilities of sequential simulators. The need for a parallel and distributed simulation environment is inevitable from a smart city perspective, especially when the entire city-wide information system is expected to be integrated with numerous services and ITS applications. In this paper, we present a conceptual model of an Integrated Distributed Connected Vehicle Simulator (IDCVS) that can emulate real-time traffic in a large metro area by incorporating hardware-in-the-loop simulation together with the closed-loop coupling of SUMO and OMNET++. We also discuss the challenges, issues, and solution approaches for implementing such a parallel closed-loop transportation network simulator by addressing transportation network partitioning problems, synchronization, and scalability issues. One unique feature of the envisioned integrated simulation tool is that it utilizes the vehicle traces collected through multiple roadway sensors? DSRC onboard unit, magnetometer, loop detector, and video detector. Another major feature of the proposed model is the incorporation of hybrid parallelism in both transportation and communication simulation platforms. We identify the challenges and issues involved in IDCVS to incorporate this multi-level parallelism. We also discuss the approaches for integrating hardware-in-the-loop simulation, addressing the steps involved in preprocessing sensor data, filtering, and extrapolating missing data, managing large real-time traffic data, and handling different data formats.

Optimal vulcanization of tires: Experimentation on idealized NR-PB natural and poly-butadiene rubber blends, phenomenological smoothed numerical kinetic model and FE implementation

An integrated simulation tool for the optimal vulcanization of tires is presented. Three are the main issues discussed on the optimal vulcanization of 3D items with complex geometry, namely: (i) the results of a preliminary realistic experimental campaign on rubber blends constituted by NR and PB in two different proportions and cured with different accelerators; (ii) a phenomenological numerical smoothing and kinetic model of interpretation of the rheometer curves experimentally obtained; (iii) the implementation of the numerical model into a commercial FE software to simulate the optimal vulcanization of car tires industrially produced. The experimental campaign is carried out on different typologies of rubber blends constituted by NR and PB at 70-30% and 50-50% concentrations, with sulfur at 1 phr and two accelerants (TBSS and DPG) at 1 and 3 phr, under standard vulcanization conditions (rheometer) at 150°, 170° and 180 °C. The numerical kinetic model uses such rheometer experimental curves to estimate kinetic constants of the cure reactions, preliminarily smoothing input data through four C1 cubic splines, with spline knots interactively selected by the user with a mouse click. Position of knots and vulcanization rates in correspondence of knots are then adjusted automatically by means of a non-linear least squares optimization procedure. In this way a set of meta-data (fitting optimally experimental values) is obtained, with a smooth prediction of the local curing rate. The kinetic approach used is characterized by three kinetic constants, describing two reactions occurring in parallel and in series and suitably accounting for possible reversion. The determination of the three kinetic constants characterizing the model is performed graphically in a quasi-analytical form. The numerical model is then nested into a Finite Element FE commercial code, to predict the crosslinking degree in real curing conditions, i.e. where the temperature is not constant. A real tire is finally analyzed during the curing process and useful indications are provided on the optimal curing temperature and time to adopt.

Impact Evaluation of In-Space Additive Manufacturing and Recycling Technologies for On-Orbit Servicing

This paper proposes an integrated simulation tool to evaluate the impact of future in-space additive manufacturing (ISAM) and recycling technologies on the responsiveness of an on-orbit servicing (OOS) infrastructure to random failures of satellites distributed over an orbit. The considered OOS infrastructure is composed of a mothership and a servicer (i.e., daughtership); the mothership serves as a depot for spares, whereas the servicer travels with the spares to randomly failed satellites and provides a service. All satellites are assumed to be modularized, and thus, the service type considered within the infrastructure is the replacement of a failed module with a new spare one. Additionally, an ISAM facility can be added to the mothership, which can scavenge material that makes up the failed module. This obtained feedstock from failed modules, along with raw material supplied from Earth, could be used to manufacture a new spare. The key parameters in this analysis include the technology level of ISAM, in terms of the types of material it can manufacture, and the scavenge rate, defined as the percent of material mass able to be recycled from the failed module to the new module. The two metrics for evaluation are the required resupply launch mass to the mothership and the average waiting time of the satellites before it is serviced. Simulation results showed that the ISAM and recycling technology provides a large impact in terms of both reduction in resupply launch mass and responsiveness of its service to the randomly failed satellites.

Evaluation of Freight Measures by Integrating Simulation Tools: The Case of Volos Port, Greece

Abstract Simulation modelling tools have been widely adopted for the evaluation of alternatives in transport planning, management and logistics. The complexity that underlies in transport systems and logistics necessitate the integration of different models that are capable of overcoming limitations that may exist individually to each model. Towards this direction, this paper aims to integrate two simulation software and use the integrated model for the evaluation of traffic and logistics measures in the wider area of Volos Port, Greece. The built model is able to simulate the traffic conditions on a transport network along with port’s intra-logistics processes and is used to evaluate a set of measures in the year 2030, by comparing it with the situation in the year 2030 without having implemented any new measure. For the evaluation, a set of indicators is used to gauge the environmental and transport impacts. The analysis is completed by using a multi-criteria decision making tool to generate the Logistics Sustainability Index (LSI) to summarize the information that is provided by the indicators. The results show that the use of integrated simulation models can provide a holistic impact evaluation of complex decisions with a high level of accuracy.