Rhys Goldstein

Coupling stochastic occupant models to building performance simulation using the discrete event system specification formalism

When applying occupant models to building performance simulation (BPS), it is common practice to use a discrete-time approach requiring fixed time steps. Consequently, a simulated occupants decisions do not increase in frequency in response to rapid changes in environmental conditions. Furthermore, as illustrated in this study through the analysis of a discrete-time EnergyPlus simulation, changing the time step between simulation runs may have a dramatic effect on BPS predictions. It is therefore necessary to adhere to a prescribed time step, which may complicate the synchronization of events when models of different domains are coupled. The main contribution of this study is an investigation of the viability of employing the discrete event system specification (DEVS) formalism to represent occupant behaviour without fixed and prescribed time steps. Results indicate that using an adaptive time advancement scheme, the DEVS formalism permits realistic patterns of decision-making while facilitating the coupling of stochastic occupant models with thermal and heating, ventilation and air-conditioning models.

Schedule-calibrated occupant behavior simulation

Building performance simulation promises to reduce the future impact of buildings on the environment by helping architects predict the energy demand associated with different design options. We present a new method for simulating occupant behavior in buildings, a key phase in the prediction of energy use. Our method first inputs the recorded activities of actual building occupants, then randomly generates fictional schedules with similar behavioral patterns. The main contribution of this work is a mathematical technique in which an arbitrary set of factors can be used to select plausible activity types, durations, and numbers of participants during a simulation. A prototype model was implemented to test the method, and results obtained to date suggest that the generated occupant schedules are believable when compared both qualitatively and quantitatively to real occupant schedules.

Vesicle-synapsin interactions modeled with Cell-DEVS

Interactions between synaptic vesicles and synapsin in a presynaptic nerve terminal were modeled using the cell-DEVS formalism. Vesicles and synapsins move randomly within the presynaptic compartment. Synapsins can bind to more than one vesicle simultaneously, causing clusters to form. Phosphorylation of synapsin reduces its affinity for vesicles, and causes the clusters to break apart. Upon dephosphosphorylation, new clusters form. Taking advantage of cell-DEVS, as opposed to traditional techniques for implementing cellular automata, the model prevents collisions between arbitrarily large clusters using transition rules restricted to a 5-cell neighborhood. Simulation results indicate that, in a qualitative sense, the behavior of vesicles and synapsin in neurons was captured.

Designing DEVS visual interfaces for end-user programmers

Although the Discrete Event System specification (DEVS) has over recent decades provided systems engineers with a scalable approach to modeling and simulation, the formalism has seen little uptake in many other disciplines where it could be equally useful. Our observations of end-user programmers confronted with DEVS theory or software suggest that learning barriers are largely responsible for this lack of utilization. To address these barriers, we apply ideas from human–computer interaction to the design of visual interfaces intended to promote their users’ effective knowledge of essential DEVS concepts. The first step is to propose a set of names that make these concepts easier to learn. We then design and provide rationale for visual interfaces for interacting with various elements of DEVS models and simulation runs. Both the names and interface designs are evaluated using the Cognitive Dimensions of Notations framework, which emphasizes trade-offs between 14 aspects of information artifacts. As a whole, this work illustrates a generally applicable design process for the development of interactive formalism-based simulation environments that are learnable and usable to those who are not experts in simulation formalisms.

Impulse-based dynamic simulation of deformable biological structures

We present a new impulse-based method, called the Tethered Particle System (TPS), for the dynamic simulation of deformable biological structures. The TPS is unusual in that it may capture a gradual process of deformation using only instantaneous impulses that occur in response to particle collisions. This paper describes the method and its application to synaptic vesicle clusters and deformable biological membranes. Unlike many alternative methods, which require solutions to systems of equations or inequalities, the calculations in a TPS simulation are all analytic. The TPS also alleviates the need to choose regular time intervals appropriate for biological entities that may differ in size by orders of magnitude. The method is promising for simulations of smallscale self-assembling deformable biological structures exhibiting random motion.

DEVS-based design of spatial simulations of biological systems

The application of the DEVS formalism to spatial simulations of biological systems is motivated by a need to keep software manageable, even when faced with complex models that may combine algorithms for potential fields, fluid dynamics, the interaction of proteins, or the reaction and diffusion of chemicals. We demonstrate DEVS-based design by applying the formalism to a “tethered particle system” (TPS), a model we designed to capture the motion of deformable biological structures. The paper focuses on the design of DEVS models using hierarchies and layers, and describes a recently-developed simulator that supports our approach. The DEVS-based TPS model, which has been used to simulate certain interactions in nerve cells, demonstrates the formalisms potential as a means of addressing the complexity of spatial biological models.

On the definition of a computational fluid dynamic solver using cellular discrete-event simulation

Abstract The Discrete Event System Specification (DEVS) has rarely been applied to the physics of motion. To explore the formalisms potential contribution to these applications, we need to investigate the definition of moving gases, liquids, rigid bodies, and deformable solids. Here, we show how to use Cell-DEVS to analyze the movement and interactions of fluids using computational fluid dynamics (CFD). We describe a set of rules that produce the same patterns as traditional CFD implementations. We present the inner workings of the CFD algorithm, the incorporation of solid barriers, and the adoption of variable time steps within the context of biomechanical simulations.

Simulation of a presynaptic nerve terminal with a tethered particle system model

Presynaptic nerve terminals are located at the ends of nerve cells; a signal propagating through a nerve cell reaches one of these compartments before being transmitted to an adjacent nerve cell. A tethered particle system (TPS) is a type of impulse-based model recently developed for the simulation of deformable biological structures. In a TPS, collisions can cause approaching particles to rebound outwards, as one would expect, but they can also caused separating particles to retract inwards. This paper demonstrates how a TPS can be used to simulate biological systems by presenting its application to a presynaptic nerve terminal. The model captures the clustering of sacs called vesicles in the presence of protein called synapsin. Both rigid and deformable membranes are also described. The simulated presynaptic nerve terminal may be used, for example, to predict how a change in synapsin concentration affects the size of vesicle clusters.

Practical aspects of the DesignDEVS simulation environment

DesignDEVS is a simulation development environment based on the Discrete Event System Specification (DEVS) formalism. This paper provides an in-depth overview of the software while focusing on the practical considerations influencing its design. Practitioners who stand to benefit from systems engineering will approach formalism-based simulation tools with little knowledge of the underlying theory. It is therefore important that theoretical principles, such as the separation of model and simulator, be emphasized by the user interface. Other practical aspects of DesignDEVS include the simplicity of atomic model code, a focus on coupling for collaboration purposes, the enforcement of essential modeling constraints, and a reliance on best practices in cases where strict enforcement might inconvenience users. In DesignDEVS, an issue we refer to as the Insidious Pointer Problem is aggressively tackled through run-time error handling. By contrast, the separation of output values from state transitions is left as a best practice for the sake of user convenience. The design decisions explained in this paper are relevant to developers of other formalism-based tools seeking widespread adoption of scalable modeling and simulation practices.

Designing Biological Simulation Models Using Formalism-Based Functional and Spatial Decompositions

One of the most daunting challenges confronting computational biologists is a problem that simulation developers in all disciplines face: the design of simulation code that can be easily understood and modified despite the complexity of the systems being modeled. To meet this challenge, the authors apply the discrete event system specification (DEVS), a general modeling formalism invented for the formal description of a wide range of systems that vary in time. Using DEVS, developers can address the complexity of a biological model by subdividing it into a hierarchy of simpler submodels. Hierarchical design is a well-known strategy for software development in general. But the question remains, what type of decomposition should be used? The authors use the upper levels of a hierarchy to separate different functions or algorithms, and then dedicate lower levels to the partitioning of space. To illustrate the approach, they present a DEVS-based model that captures the 3D self-assembly of vesicle clusters and their role in the propagation of information between nerve cells.