Programs and Communities

Phoenix is the sixth most populated city in the United States and the 12th largest metropolitan area by population, with about 4.4 million people. As the region continues to grow, the demand for housing and jobs within the metropolitan area is projected to rise under uncertain climate conditions.

Undergraduate and graduate students from Engineering, Sustainability, and Urban Planning in ASU’s Urban Infrastructure Anatomy and Sustainable Development course evaluated the water, energy, and infrastructure changes that result from smart growth in Phoenix, Arizona. The Maricopa Association of Government's Sustainable Transportation and Land Use Integration Study identified a market for 485,000 residential dwelling units in the urban core. Household water and energy use changes, changes in infrastructure needs, and financial and economic savings are assessed along with associated energy use and greenhouse gas emissions.

The course project has produced data on sustainable development in Phoenix and the findings will be made available through ASU’s Urban Sustainability Lab.

Hybrid system models - those devised from two or more disparate sub-system models - provide a number of benefits in terms of conceptualization, development, and assessment of dynamical systems. The decomposition approach helps to formulate complex interactions that are otherwise difficult or impractical to express. However, hybrid model development and usage can introduce complexity that emerges from the composition itself.

To improve assurance of model correctness, sub-systems using disparate modeling formalisms must be integrated above and beyond just the data and control level; their composition must have model specification and simulation execution aspects as well. Poly-formalism composition is one approach to composing models in this manner.

This dissertation describes a poly-formalism composition between a Discrete EVent System specification (DEVS) model and a Cellular Automata (CA) model types. These model specifications have been chosen for their broad applicability in important and emerging domains. An agent-environment domain exemplifies the composition approach. The inherent spatial relations within a CA make it well-suited for environmental representations. Similarly, the component-based nature of agents fits well within the hierarchical component structure of DEVS.

This composition employs the use of a third model, called an interaction model, that includes methods for integrating the two model types at a formalism level, at a systems architecture level, and at a model execution level. A prototype framework using DEVS for the agent model and GRASS for the environment has been developed and is described. Furthermore, this dissertation explains how the concepts of this composition approach are being applied to a real-world research project.

This dissertation expands the tool set modelers in computer science and other disciplines have in order to build hybrid system models, and provides an interaction model for an on-going research project. The concepts and models presented in this dissertation demonstrate the feasibility of composition between discrete-event agents and discrete-time cellular automata. Furthermore, it provides concepts and models that may be applied directly, or used by a modeler to devise compositions for other research efforts.

In the spring of 2016, the City of Apache Junction partnered with the School of Geographical Sciences and Urban Planning at Arizona State University on three forward-thinking plans for development in Apache Junction. Graduate students in the Urban and Environmental Planning program worked alongside City staff, elected officials and the public to identify opportunities and visions for:
       1. Multi-modal access and connectivity improvements for City streets and open space.
       2. Downtown development.
       3. A master-planned community on state land south of the U.S. 60.

The following sections of the report present Apache Junction’s unique characteristics, current resident demographics, development needs and implementation strategies for each project:
       1. Community Profile
       2. Trail Connectivity Master Plan
       3. Downtown Visioning
       4. State Land Visioning

The Trail Connectivity Master Plan optimizes existing trails and wide road shoulders to improve multi-modal connections across the city. The proposed connections emphasize access to important recreation, education and other community facilities for pedestrians, equestrians and bicycles. Trail and lane designs recommend vegetated buffers, wherever possible, to improve traveler safety and comfort. The proposals also increase residents’ interaction with open space along urban-rural trails and park linkages to preserve opportunities to engage with nature. The objectives of the report are accomplished through three goals: connectivity, safety improvements and open space preservation.

Downtown Visioning builds on a large body of conceptual design work for Apache Junction’s downtown area along Idaho Road and Apache Trail. This report identifies three goals: to establish a town center, to reestablish the grid systems while maintaining a view of the Superstition Mountains, and to create an identity and sense of place for the downtown.

State Land Visioning addresses a tract of land, approximately 25 square miles in area, south of the U.S. 60. The main objective is to facilitate growth and proper development in accordance with existing goals in Apache Junction’s General Plan. This is accomplished through three goals:
       1. Develop a foundation for the creation of an economic corridor along US-60 through
           preliminary market research and land use planning.
       2. Create multi-modal connections between existing development north of US-60 and
           future recreational space northeast of US-60.
       3. Maintain a large ratio of open space to developed area that encompasses existing
           washes and floodplains using a master planned community framework to provide an
           example for future land use planning.