As architectural design and construction projects tend to tackle larger scales and become more complex, the multiple involved disciplines in the Architecture, Engineering and Construction (AEC) sector often need to work globally from different remote locations. This increased complexity impacts digital design up until to fabrication workflows, which become more challenging and discontinuous, as each industry partner involved in the construction of a given project operates on different software environments and needs to access the precise fabrication data of specific design components. Consequently, managing and keeping track of design changes and data flow throughout the whole design process still remains a challenging task. This paper discusses how this particular challenge can be tackled through the development of a web-based interactive Activity Network Diagram (AND) - named SpeckleViz - that continuously maps the data transfers of the design and building processes, enabling the end-user to explore, interact and get a better understanding of the constantly evolving digital design workflow. Through this paper, the authors qualify an "end-user" as an advanced or expert user that performs complex geometry modelling tasks within wider collaborative workflows involving other advanced end-users. SpeckleViz (2020) is an application built upon Speckle (2020), an open-source data platform for the AEC. We illustrate the usefulness of interactive visualization of ANDs in the development of digital design workflows.
A collaborative research on optimization of a main rotor blade for helicopters by JAXA, ONERA and DLR is underway. As a first step, blade optimization method with five design variables is explored by dealing with hovering conditions. Optimizations and simulations are carried out by each agency with their own analysis codes and these results are cross-validated. This paper presents an overview of the project and an interim report on the results obtained so far.
Speech intelligibility is crucial in many spaces, yet designers often fail to predict the acoustic shortcomings of certain design choices. This paper builds on the potential of hybrid surface treatments showcasing low-frequency absorption to control background noise levels and high-frequency diffusion to improve speech-in-noise perception to introduce a workflow that encodes this information in a format easily perceived by designers. After patterns are being classified based on periodicity into partly periodic, non-periodic or aperiodic, a matrix serves as a rule of thumb communicating to non-experts the critical variables for high-frequency diffusion, such as well depth sequence, scale and profile. These become inputs of a computational process that generates variations to tailor patterns for speech intelligibility. Lastly, plotted graphs that visualize quantitative figures obtained from simulations are marked by a bounding box relative to the effective frequency range for designers to evaluate examined patterns during the process of optioneering. This integrated workflow targets architects and designers that seek for visual feedback to support an iterative exploration of performance driven geometries, while recognizing the contribution of aperiodic order to uniformly distribute the flow of sound energy.
Additive manufacturing allows the fabrication of complex geometries with enhanced performances, making it interesting for application in facade components. Assessing the performance of non-standard geometries and 3D printed parts requires a combination of digital and analytical methods to retrieve validated models which can guide the design process. In this study a 3D printed mono-material facade component was designed, where the complex geometrical configuration enhance its thermal insulation properties. For this, a digital workflow was developed, encompassing performance-driven design, performance assessment and geometry generation for fabrication. Analytical heat transfer models, heat flux measurements, and heat transfer simulations with COMSOL Multiphysics were used to assess the thermal properties of different geometrical alternatives. By observing and comparing the results, a validated model was defined to retrieve design guidelines and thermal performance indicators. The results identify porosity as the driving factor for thermal insulation and clarify the nature of the heat transfer in 3D printed cellular structures. Open surface-based geometries were preferred for the good combination of thermal properties and manufacturability. The findings are embedded in a digital workflow in Rhino-Grasshopper, enabling the design of insulating cellular structures to be used in 3D printed facade components.
Findings from cognitive science link the architectural complexity of multilevel buildings with occupants’ difficulty in orienting and finding their way. Nevertheless, current approaches to modelling occupants’ wayfinding reduce the representation of 3D multilevel buildings to isolated 2D graphs of each floor. These graphs do not take account of the interplay between agents’ 3D field of view and buildings’ 3D geometry, topology, or semantics, yet these are necessary to inform occupants’ path differentiation during wayfinding. Instead, agents are often modeled as unbounded and rational, able to calculate complete paths towards goals that are not immediately visible using direct routing algorithms. In turn, simulated behavior in most cases is unrealistically optimal (e.g. shortest or fastest route). This gap may hinder architects’ ability to foresee how their design decisions may result in suboptimal wayfinding behavior, whether intended or not. To bridge this gap, the paper presents cogARCH, a computational, agent-based simulation framework. cogARCH is grounded in research on spatial cognition and heuristic decision making to support pre-occupancy evaluation of wayfinding in multilevel buildings. To demonstrate the relevance of cogARCH to architectural design, we apply it to assess wayfinding performance across three architectural variations of a multilevel education building. Preliminary results showcase significant variability in cognitive agents’ wayfinding performance between building scenarios. In contrast, behavior of shortest-path agents sampled across respective conditions displayed significantly less variance and thus failed to reflect potential effects of architectural changes applied to 3D building configuration on wayfinding behavior.
Discrete-event process simulation now has a long and distinguished history of supporting the improvement of manufacturing processes. From those origins, it has expanded its applicability to supply chains, service industries, health care, and public transport. In manufacturing contexts, simulation modeling and analysis regularly helps fine-tune the trade-off between high inventory versus danger of stockout, improve and balance machine utilization, schedule workers more effectively, and improve performance metrics such as average and maximum times in queue and average and maximum length of queues. In the present work, the authors describe a successful application of simulation to the manufacture of footwear. The original manufacturing process was beset by problems including low throughput, high headcount, overly high or low machine utilization, unduly large rejection rates, and ergonomic concerns. The simulation and analysis project described in this paper guided significant improvements, including doubling the output while reducing worker headcount to two-thirds of its initial value.
The priority queue implementation holding the list of future events is central to discrete event simulations. Mobile computing now allows the possibility of executing online discrete event simulations that are driven by dynamic real time data. The simulation system must be energy efficient in order to be effectively deployed in energy constrained environments such as mobile systems operating from battery power. Memory hierarchy and memory access plays a critical role on the overall energy consumption of priority queue implementations. This paper investigates the effect that memory access has on power consumption for four priority queue implementations: linked list, implicit heap, explicit heap, and splay tree.
Organizations continually seek to understand the components of cyber risk. A major part of this is understanding how employee behavior influences this risk. In this paper, we examine the connection between an organization's cyber risk and the level of cyberloafing in its employee population. Cyberloafing, the practice of using company resources for non-work-related internet activities, effects a company's overall productivity and creates an opportunity for malware to be introduced into the corporate system. Productivity, workload, and corporate sanctions have varying effects on the level of cyberloafing and therefore an impact on the cyber risk. We create a generic System Dynamics model to capture this nonlinear relationship and examine a use-case of minor cyberloafing (e.g., social media usage) in organizations. We discover that, while sanctions play a role in mitigating cyberloafing, workload influences on cyberloafing tendencies are more impactful.
We have recently witnessed the proliferation of large-scale behavioral data that can be used to empirically develop agent-based models (ABMs). Despite this opportunity, the literature has neglected to offer a structured agent-based modeling approach to produce agents or its parts directly from data. In this paper, we present initial steps towards an agent-based modeling approach that focuses on individual-level data to generate agent behavioral rules and initialize agent attribute values. We present a structured way to integrate Big Data and machine learning techniques at the individual agent-level. We also describe a conceptual use-case study of an urban mobility simulation driven by millions of geo-tagged Twitter social media messages. We believe our approach will advance the-state-of-the-art in developing empirical ABMs and conducting their validation. Further work is needed to assess data suitability, to compare with other approaches, to standardize data collection, and to serve all these features in near-real time.
Modeling approaches can support policy coherence by capturing the logistics of an intervention involving multiple individuals, or by identifying goals and preferences of each individual. An important intermediate step is to identify agreement among individuals. This may be achieved through intensive qualitative methods such as interviews, or by automatically comparing models. Current comparisons are limited as they either assess whether individuals think of the same factors, or see the same causal connections between factors. Systems science suggests that, to test whether individuals really share a paradigm, we should mobilize their whole models. Instead of comparing their whole models through multiple simulation scenarios, we suggested using network centrality. We performed experiments on mental models from 264 participants in the context of fishery management. Our results suggest that if stakeholder groups agree on the central factors (per Katz centrality), they also tend to agree on simulation outcomes and thus share a paradigm.
In this paper, we introduce the concept of digital senses as an approach for integrating the real world with the digital world. We define the real world as the world we access directly through our senses and the digital world as the world we access through a man-made interface. We show how 1) the concept of digital senses helps people outside the standard sensory spectrum (low vision, low hearing, etc.) interact with both the real and digital world and 2) how it might help generate empathy with people or situations in the past or future. We describe how we use digital senses to 1) reenact a day in the life of the ancient city of Catalhoyuk; 2) follow an automaton through time and showcase its changing role in people's life. Finally, we discuss issues and challenges associated with the technical implementation of digital senses.
A common deployment strategy for wireless sensor networks is to position sensors according to a probabilistic distribution. Some sensor distributions offer advantages in redundancy, which helps ensure network survivability even with the loss of multiple sensor nodes to cyber attack. Properly selecting an initial sensor deployment distribution mitigates the threat of a denial of service (DoS) attack. While it is clear that some distributions are superior to others, it is not clear how to select the best sensor distribution as a defensive measure. Current strategies rely on mathematical analysis and are restricted to a subset of possible distributions. This paper examines the problem from an experimental perspective. We propose a novel method for evaluating how a given sensor deployment pattern may withstand a DoS attack based on agent-based simulation. We have implemented a first prototype of our model and illustrate its feasibility as part of a future decision support system.
The provision and distribution of electricity are necessary for the good functioning of society. According to the US Department of Energy (2015), the electricity systems should be (1) reliable, (2) economically competitive and (3) environmentally responsible. Such a vision is not easily achievable, as these qualities may be in conflict with one another. Power system models are essential to simulate changes in the system and help resolve or mitigate conflicts. In this study, we present a gaming simulation, built upon a bottom-up discrete-event system model, to simulate the behavior and interactions of the main components in a power grid, forming various architecture scenarios. To develop this framework, we consider three main actions which the player can take, namely build, and retire, to work toward an architecture with a more balanced weight of grid quality.
Reversible random number generations are useful in large-scale fault-tolerant parallel computations and parallel discrete event simulations that are based on reversible computation. The Universal Non-Uniform Random Number Generator (UNU.RAN) is one of the popular random number generators used in the simulation community, but the generators are forward-only in nature. In this paper, we develop new reverse algorithm for the default uniform random number generator algorithm of UNU.RAN and also a few non-uniform random generators that use the Transform Density Reduction (TDR) method. We verify the correctness of reversals of our algorithms and also provide performance results to demonstrate reverse computing runtime adds little overheads relative to its forward counterpart.
The academic achievement gap is a persistent phenomenon in U.S. education system despite a long history of efforts and billions of dollars spent to correct it. Literature abounds with theories about why the gap exist, such as: student self-perception, parent involvement, teacher quality, and others. Model based approaches have been used to understand various aspects of the phenomenon. However, no models were identified that consider a comprehensive set of theories, and is specifically designed to investigate potential policies and strategies for reducing the gap. We build such a model using a methodology that includes: a) Modeling and Simulation-System Development Framework (MS-SDF); b) Systems Modeling Language (SysML); and c) a Systems Dynamics approach. Preliminary findings indicate that concepts from prevailing theories about the achievement gap can be accurately represented in a single system dynamics model. We also identify key stakeholders, functions, and variables affecting the achievement gap.
This paper evaluates the state of the art of hybrid simulation support for cyber physical systems. The traditional definition for hybrid simulation is expanded to include recent research on multi-paradigm and other multi-faceted modeling approaches. Based on the review of current approaches, the focus of simulation support lies first in providing a virtual environment supporting development and testing, and second on utilizing simulation as part of the cyber physical system. A literature research on support of cyber physical systems within the simulation community shows common trends towards a common formalism, but an aligned research agenda has not been established.
