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The workshop is composed of two main parts: the first part devoted to atomistic Monte Carlo simulations and the second part devoted to the Phase Field modelling. In each part a lecture will be accompanied by exercise activities.

Mathematical models of regulatory networks become more difficult to construct and understand as they grow in size and complexity. Large regulatory network models can be built up from smaller models, representing subsets of reactions within the larger network. This dissertation focuses on novel model construction techniques that extend the ability of biological modelers to construct larger models by supplying them with tools for decomposing models and using the resulting components to construct larger models. Over the last 20 years, molecular biologists have amassed a great deal of information about the genes and proteins that carry out fundamental biological processes within living cells --- processes such as growth and reproduction, movement, signal reception and response, and programmed cell death. The full complexity of these macromolecular regulatory networks is too great to tackle mathematically at the present time. Nonetheless, modelers have had success building dynamical models of restricted parts of the network. Systems biologists need tools now to support composing "submodels" into more comprehensive models of integrated regulatory networks. We have identified and developed four novel processes (fusion, composition, flattening, and aggregation) whose purpose is to support the construction of larger models. Model Fusion combines two or more models in an irreversible manner. In fusion, the identities of the original (sub)models are lost. Beyond some size, fused models will become too complex to grasp and manage as single entities. In this case, it may be more useful to represent large models as compositions of distinct components. In Model Composition one thinks of models not as monolithic entities but rather as collections of smaller components (submodels) joined together. A composed model is built from two or more submodels by describing their redundancies and interactions. While it is appealing in the short term to build larger models from pre-existing models, each developed independently for their own purposes, we believe that ultimately it will become necessary to build large models from components that have been designed for the purpose of combining them. We define Model Aggregation as a restricted form of composition that represents a collection of model elements as a single entity (a "module"). A module contains a definition of pre-determined input and output ports. The process of aggregation (connecting modules via their interface ports) allows modelers to create larger models in a controlled manner. Model Flattening converts a composed or aggregated model with some hierarchy or connections to one without such connections. The relationships used to describe the interactions among the submodels are lost, as the composed or aggregated model is converted into a single large (flat) model. Flattening allows us to use existing simulation tools, which have no support for composition or aggregation. / Ph. D.

The effect of center of gravity (CG) height and lateral and longitudinal off-centering on high-speed roll stability of A-double tractor trailers with 28-ft and 33-ft straight-rail and drop-frame trailers is evaluated through simulation and track testing. The changes in CG position due to the type of trailer (straight-rail vs. drop-frame) and laterally and longitudinally off-centered loads are considered. The simulation results show that imbalanced trailer loading induces roll instability and increases the likelihood of trailer rollover. Additionally, for equal loading conditions, the drop-frame trailers exhibit better roll stability than straight-rail trailers because of the lower CG. The simulation evaluation of 28-ft A-doubles is complemented with track testing of 33-ft trailers in alike (Drop-Drop and Straight-Straight) and mixed (Drop-Straight and Straight-Drop) arrangements of front and rear trailers, for various steering maneuvers that represent highway driving, such as exit ramp, obstacle avoidance, etc. The test trailers include specially designed load frames for emulating a loaded trailer in various loading conditions, outriggers for preventing trailer rollover, and durability structures for withstanding the torsional and bending moments resulting from the tests. Various sensors, including GPS, LiDAR units, accelerometers, string pots, and pressure transducers, are used, along with an onboard data acquisition (DAQ) system, for collecting the necessary data for post-analysis. Analysis of the test data indicates that the Drop-Drop configuration exhibits higher roll stability than the Straight-Straight configuration. For mixed trailers, the Drop-Straight configuration exhibits higher roll stability in exit ramps, but lower obstacle avoidance stability. Equipping the trailers with a roll stability control (RSC) system improves roll stability in terms of increasing the rollover threshold speed and tolerating more aggressive lane change steering maneuvers for A-doubles in various conditions. The RSC performance increases further when the brake application is synchronized between the two trailers to account for any lateral dynamic delay that naturally occurs. A novel interconnected RSC system is proposed to eliminate the lag between the RSC modules with a new control logarithm. The proposed RSC system increases the trailers' roll stability by 16% when compared with independent RSC systems that are commonly used for A-doubles. / Doctor of Philosophy / Commercial trucks play an indispensable role in transporting goods in society. A large percentage of the goods that we use daily or are delivered to our homes are transported on the nation's highways. Most often, the average automobile driver notices the presence of trucks on highways, at times with a bit of disdain. The public's perception appears to be formed by the fact that accidents involving commercial trucks are more publicized because they can cause more property damage, injuries, or even fatalities. The primary thrust of this research is to make the nation's highways safer by offering a better understanding of the dynamics of trucks with double trailers that are operated with a higher frequency on public highways. The double trailer configuration is often favored because of its larger cargo capacity and high modularity. However, their roll dynamics are not as well understood as the conventional tractor-semitrailers. Understanding the dynamics of double-trailer trucks is undoubtedly the very first step toward preventing or reducing the traffic accidents caused by rollovers. This study provides detailed analysis of roll dynamics for double trailers with imbalanced payloads. It also evaluates the effect of different types of trailers, such as drop-frame trailers (those with a "belly" in the mid-section of the trailer) and straight-rail trailers (those without a "belly") on their rollover propensity. The commercialized RSC system is evaluated for its effectiveness on the double-trailer truck. The evaluations are based on over 1,000 sets of tests in highly controlled conditions at the Transportation Research Center (TRC), a special facility for vehicle dynamic assessment in East Liberty, Ohio. It is found that the rollover dynamics of trucks with double trailers can be improved by having an awareness of the most favorable trailer arrangements according to their types of trailers and type of steering (exit-ramp or obstacle avoidance). In addition, this study provides the analysis of the commercialized RSC system for its effectiveness on the double-trailer truck. Lastly, a novel RSC system is proposed to further improve the effectiveness of the original RSC system.

Social contact networks represent proximity relationships between individual agents. Such networks are useful in diverse applications, including epidemiology, wireless networking and urban resilience. The vertices of a social contact network represent individual agents (e.g. people). Time varying edges represent time varying proximity relationship. The networks are relational -- node and edge labels represent important demographic, spatial and temporal attributes. Synthesizing social contact networks that span large urban regions is challenging for several reasons including: spatial, temporal and relational variety of data sources, noisy and incomplete data, and privacy and confidentiality requirements. Moreover, the synthesized networks differ due to the data and methods used to synthesize them. This dissertation undertakes a systematic study of synthesizing urban scale social contact networks within the specific application context of computational epidemiology. It is motivated by three important questions: (i) How does one construct a realistic social contact network that is adaptable to different levels of data availability? (ii) How does one compare different versions of the network for a given region, and what are appropriate metrics when comparing the relational networks? (iii) When does a network have adequate structural details for the specific application we have. We study these questions by synthesizing three social contact networks for Delhi, India. Our case study suggests that we can iteratively improve the quality of a network by adapting to the best data sources available within a framework. The networks differ by the data and the models used. We carry out detailed comparative analyses of the networks. The analysis has three components: (i) structure analysis that compares the structural properties of the networks, (ii) dynamics analysis that compares the epidemic dynamics on these networks and (iii) policy analysis that compares the efficacy of various interventions. We have proposed a framework to systematically analyze how details in networks impact epidemic dynamics over these networks. The results suggest that a combination of multi-level metrics instead of any individual one should be used to compare two networks. We further investigate the sensitivity of these models. The study reveals the details necessary for particular class of control policies. Our methods are entirely general and can be applied to other areas of network science. / Ph. D.

Dynamics of social processes in populations, such as the spread of emotions, influence, opinions, and mass movements (often referred to individually and collectively as contagions), are increasingly studied because of their economic, social, and political impacts. Moreover, multiple contagions may interact and hence studying their simultaneous evolution is important. Within the context of social media, large datasets involving many tens of millions of people are leading to new insights into human behavior, and these datasets continue to grow in size. Through social media, contagions can readily cross national boundaries, as evidenced by the 2011 Arab Spring. These and other observations guide our work. Our goal is to study contagion processes at scale with an approach that permits intricate descriptions of interactions among members of a population. Our contributions are a modeling environment to perform these computations and a set of approaches to predict contagion spread size and to block the spread of contagions. Since we represent populations as networks, we also provide insights into network structure effects, and present and analyze a new model of contagion dynamics that represents a person\'s behavior in repeatedly joining and withdrawing from collective action. We study variants of problems for different classes of social contagions, including those known as simple and complex contagions. / Ph. D.

Cloud-based Integrated Development Environments (IDEs) are highly complex systems compared to stand-alone IDEs that are installed on client devices. Today, the visual simulation environments developed as services on the cloud can offer similar features as client-based IDEs thanks to the advancements to the cloud technologies. However, most of the existing visual simulation tools are developed for client-based systems. Moving towards the cloud for visual simulation environments can provide better collaboration for simulation developers, easy access to the software, and less client hardware dependency. Proper guidance for the development of visual simulation tools can help researchers to develop their tools as a service on the cloud. This thesis presents a Cloud-based visuAl simulatioN enVironment for trAffic networkS (CANVAS), providing a framework that tackles challenges on the cloud-based visual simulation tools. CANVAS offers a set of tools for the composition and visualization of simulation models for the traffic network problem domain. CANVAS uses an asynchronous visualization protocol with efficient resource utilization on the server, enabling concurrent usage of the IDE. The simulation is executed on the server while the visualization is processed on the client-device within web browsers enabling execution-heavy simulations to thin clients. The component-based architecture of CANVAS offers a fully decoupled system that provides easier development and maintenance. The architecture can be used for the development of other cloud-based visual simulation IDEs. The CANVAS design and asynchronous visualization protocol show that advanced visualization capabilities can be provided to the client without depending on the client hardware. / Master of Science / Doing things “in the cloud” has become ubiquitous. The term “in the cloud” implies that a software application runs on a server computer somewhere in the world and a user with a web browser uses it over the Internet on a computer such as desktop or laptop. This thesis addresses the problem of how to create and execute a visual simulation of a system all “in the cloud”. We developed a system called cloud-based visual simulation environment for traffic networks (CANVAS). We selected traffic networks as an example problem domain to illustrate the capabilities of CANVAS. A person interested in creating and executing a visual simulation of a traffic network “in the cloud” can use CANVAS. Using a web browser on an Internet-connected computer, the user can develop and execute a visual simulation of a traffic network with the tools made available in CANVAS.

The history and trajectory of the human race is inseparable from our innate need to explore the unknown. As human exploration drives boundless new insights into the universe, characterization and accurate modeling methods are required to develop the next generation of exploratory vehicles to map and analyze foreign lands. As such the presented work looks to provide characterization and modeling approaches for unsteady aerodynamic phenomena in the extraterrestrial environments of Mars and Titan. Specifically, unsteady aerodynamic loads including dynamic stall are characterized using high-fidelity numerical experiments to better understand the effects of low Reynolds number and high Mach number flows on the process. Additionally, modeling of unsteady aerodynamic behavior at low Reynolds numbers similar to those observed when designing the Mars ingenuity rotorcraft are developed and extensively evaluated. Lastly, the characterization and multi-fidelity modeling of unsteady aerodynamic effects under Titan atmospheric conditions is conducted for a coaxial rotor system.

Incorporating insulation material with phase change materials (PCMs) could help enhance the insulation capability for a refrigerator system. The phase change material can absorb or release large amount of latent heat of fusion depending on surrounding temperatures for efficient thermal management. This research focuses on how incorporating PCM to the conventional PU foam insulation affects the inside temperatures of the refrigerator system and in-turn helps in conserving energy by reducing the compressor run time. It was found that only 0.25-inch-thick PCM layer in insulation can certainly benefit the refrigerators by reducing the amount of electricity consumption and thus increasing the total energy savings through the numerical study results via COMSOL Multiphysics in this study. This work aims to investigate a PCM-incorporated insulation material to accomplish the enhancement of thermal insulation performance for refrigerators.

The goal of the work reported herein has been to model aspects of the electrical distribution system of an all-electric ship (AES) and to couple electrical load behavior with the thermal management network aboard the ship. The development of a thermally dependent electrical network has built upon an in-house thermal management simulation environment to replace the existing steady state heat loads with dynamic, thermally dependent, electrical heat loads. Quantifying the close relationship between thermal and electrical systems is of fundamental importance in a large, integrated system like the AES. This in-house thermal management environment, called the Dynamic Thermal Modeling and Simulation (DTMS) framework, provided the fundamental capabilities for modeling thermal systems and subsystems relevant to the AES. The motivation behind the initial work on DTMS was to understand the dynamics of thermal management aboard the ship. The first version, developed in 2007, captured the fundamental aspects of system-level thermal management while maintaining modularity and allowing for further development into other energy domains. The reconfigurable nature of the DTMS framework allowed for the expansion into the electrical domain with the creation of an electrical distribution network in support of thermal simulations. The dynamics of the electrical distribution system of the AES were captured using reconfigurable and physics-based circuit elements that allow for thermal feedback to affect the behavior of the system. Following the creation of the electrical network, subsystems and systems were created to simulate electrical distribution. Then, again using the modularity features of DTMS, a thermal resistive heat flow network was created to capture the transient behavior of heat flow from the electrical network to the existing thermal management framework. This network provides the intimate link between the thermal management framework and the electrical distribution system. Finally, the three frameworks (electrical, thermal resistive, and thermal management) were combined to quantify the impact that each system has relative to system-level operation. Simulations provide an indication of the unlimited configurations and potential design space a user of DTMS can explore to explore the design of an AES. / text