SIMULATION: Transactions of The Society for Modeling and Simulation International

Ramajo, Damian; Corzo, Santiago

doi: 10.1177/00375497221151168pmid: N/A

The HVAC systems in closed buses promote high particle spread. Lagrangian particle tracking simulations were carried out to evaluate airborne COVID transmission through droplets emitted by sneezing while Eulerian simulations were performed to account for the spread of aerosols emitted by breathing. The position of passengers as well as the effect of three HVAC configurations were evaluated. On one hand, it was concluded that large droplets can travel more than 3 m without being significantly affected by the inflow conditions, but small droplets are easily dispersed by the airflow, and many of them are captured by the HVAC systems. On the other hand, the HVAC systems quickly spreads aerosols along the whole of the bus, increasing the average risk for all passengers, but sensibly reducing the high local risks observed under motionless inflow conditions. The transmission risk was calculated by applying the Wells-Riley model, concluding that the transmission risk for a 20-min trip could remain below 0.5% if HVAC configurations with many inlet/outlet vents are implemented, and the passengers remain in silence and wear face masks.

Chatterjee, Sohom; Hebaish, Youssef; Ntaimo, Lewis; Deegear, James; Rucker, Miles; Aprahamian, Hrayer

doi: 10.1177/00375497231159675pmid: N/A

College counseling centers in various universities have been tasked with the important responsibility of attending to the mental health needs of their students. Owing to the unprecedented recent surge of demand for such services, college counseling centers are facing several crippling resource-level challenges. This is leading to longer wait times which limit access to critical mental health services. To address these challenges, we construct a discrete-event simulation model that captures several intricate details of their operations and provides a data-driven framework to quantify the effect of different policy changes. In contrast to existing work on this matter, which is primarily based on qualitative assessments, the considered quantitative approach has the potential to lead to key observations that can assist counseling directors in constructing a system with desirable performance. To demonstrate the benefit of the considered simulation model, we use data specific to Texas A&M’s Counseling & Psychological Services to run a series of numerical experiments. Our results demonstrate the predictive power of the simulation model, highlight a number of key observations, and identify policy changes that result in desirable system performance.

Djeffal, Selman; Mahfoudi, Chawki

doi: 10.1177/00375497231164645pmid: N/A

Multi-section continuum robots’ (CRs) behavior is still an outstanding problem because of the highly non-linearity of its equation of motions. To this end, in this paper, particle swarm optimization (PSO) is adopted to solve the inverse kinematic model (IKM) of CRs. First, the CR’s structure is properly described. Then, the aforementioned algorithm is elaborately discussed and implemented in figuring out the IKM of CR and verified through forward kinematic model by choosing the PSO parameters, namely, cognitive factors (C1=C2=1.2) and inertia weight (ω=0.79) for 200 positions on an arc-like trajectory. The optimal angle values (θ=0.0346 and φ=0.00013) which ensure the lowest distance between the attainably desired position and the robot’s end effector are 1.04497×10−9mm which is perfectly accurate. After that, simulation through MATLAB is carried out, namely, in the first simulation, a three-section CR follows a linear trajectory with a precision approximately equal to 0.75×10−9mm. Furthermore, PSO takes 7 ms as a mean consumption time to make the robot’s end effector attain to each position. Then, a circular trajectory is followed using PSO. Comparatively speaking, PSO is compared with four meta-heuristic approaches; it is remarked that PSO is a good compromise between accuracy and time consumption. Based on the obtained results, PSO can be considered as a trade-off between accuracy and time consumption for solving the IKM of CRs with complex structure.

Stolpe, Audun; Rummelhoff, Ivar; Hannay, Jo Erskine

doi: 10.1177/00375497231157384pmid: N/A

Simulation games are designed to cultivate expertise and rehearse particular skill sets. To yield longitudinal effects, sequences of events must be crafted to yield intended learning outcomes, sometimes by focusing on particularly difficult situations and replaying variants. The present paper develops a logic-based approach for encoding the interrelation between action, events, and objects in a manner that allows the resulting scenario description to immediately be executed in a game development environment. This has the dual effect of decoupling the description of a scenario from the simulation platform itself, as well as supporting iterative and flexible development of learning content. To this end, we provide three interrelated components: First, we develop a scenario description language based on Answer Set Programming. The language is designed to allow an automated reasoner to deduce a schedule of the future events that are caused by an action taken in a given simulation environment. Second, we define a protocol for exchanging actions and computed futures between, respectively, the simulation environment and the external automated reasoner. Finally, as a proof of concept, we develop an Application Programming Interface (API) for the Unity Real-Time Development Platform that implements the protocol and offers a software framework for connecting the computed future events to concrete game objects. This allows the game to evolve coherently from the specification. We argue that the resulting system inherits capabilities for artificial commonsense reasoning from its declarative basis which are useful for reasoning about an evolving emergency incident or training scenario.

Reiher, David; Hahn, Axel

doi: 10.1177/00375497231152651pmid: N/A

Modern highly automated and autonomous traffic systems and sub-systems require new approaches to test their functional safety in the context of validation and verification. One approach that has taken a leading role in current research is scenario-based testing. For various reasons, simulation is considered to be the most practicable solution for a wide range of test scenarios. However, this is where many existing simulation systems in research reach their limits. In order to be able to integrate the widest possible range of systems to be tested into the simulation, the use of co-simulation has proven to be particularly useful. In this work, the High-Level Architecture defined in the IEEE 1516-2010 standard is specifically addressed, and a concept is developed that establishes the foundation for the feasible use of scenario-based distributed co-simulation on its basis. The main challenge identified and addressed is the resolution of the double-sided dependency between scenario and simulation models. The solution was to fully automate the generation and instantiation of the simulation environment on the basis of a scenario instance. Finally, the developed concept was implemented as a prototype, and the resulting process for its use is presented here using an example scenario. Based on the experience gained during the creation of the concept and the prototype, the next steps for future work are outlined in conclusion.