Up until now, most of the models developed to optimize biomass supply chains have failed to quantify the effect of biomass quality and the preprocessing operations required to meet biomass specifications on overall cost and performance. However, the IBSAL-SimMOpt method provides a novel approach for finding near-optimal solutions to the problem of designing biomass supply chains that improve the physical characteristics of the feedstock at an acceptable cost. The bioenergy sector and the research community now have access to a simulation-based optimization model with activity-based costing that is capable of representing the stochastic behavior of some elements intervening in the corn stover supply chain for the production of bioethanol. This analytical model can be used for decision making as well as educational and training purposes since it allows the user to conduct “what if” scenarios.

Incorporating non-traditional feedstocks, e.g., biomass, to chemical process industry (CPI) requires investments in research & development (R&D) and capacity expansions. The impact of these investments on the evolution of biomass to commodity chemicals (BTCC) system should be studied to ensure a cost-effective transition with acceptable risk levels. The BTCC system includes both exogenous, e.g., product demands (decision-independent) and endogenous, e.g., the change in technology cost with investment levels (decision-dependent) uncertainties. This report presents a prototype simulation-based optimization (SIMOPT) approach to study the BTCC system evolution under exogenous and endogenous uncertainties, and provides a preliminary analysis of the impact of using three different sampling methods, i.e., Monte Carlo, Latin Hypercube, and Halton sequence, to generate the simulation runs on the computational cost of the SIMOPT approach. The results of a simplified case study suggest that annual demand increases is the dominant factor for the total cost of the BTCC system. The results also suggest that using Halton sequence as the sampling method yields the smallest number of samples, i.e., the least computational cost, to achieve a statistically significant solution

The Potomac Reservoir and River Simulation Model (PRRISM) was originally developed using Fortran by a research team at Johns Hopkins University in 1982. In the late 1990’s, the CO-OP section of the Interstate Commission on the Potomac River Basin (ICPRB) converted the model to an ExtendSim model. PRRISM simulates the physical processes and operations of four reservoirs and the allocation of water within the Washington Metropolitan Area (WMA) at daily time scale. It determines the amount of water available to each of the several jurisdictions, for given streamflows, demands, and weather allocation and reservoir operation rules. When operating in batch mode, PRRISM performs the functions of a regional water supply manager in strict accordance with rules specified by the model user. This interactive model allows participants to engage in a dialogue with the model as it is being executed, changing model parameters and overriding prespecified decision rules. Today PRRISM is a deterministic continuous simulation model that is regularly updated to reflect system changes. This model continues to serve as a long-term planning tool with which water supply management decisions are made.

Blue Plan-it takes an agency’s vast quantity of data, including maintenance, geographic, regulatory, and financial information, and creates a customized graphical user interface that can be easily modified, understood, and presented.

Developed by Carollo to help their clients manage complex, interconnected water and wastewater infrastructure, storage, treatment, conveyance, and distribution systems, Blue Plan-it is a fully customizable simulation and optimization model suite developed in ExtendSim. Featured with a simple but powerful “Drag and drop” interface, Blue Plan-it allows for rapid model configuration by dragging blocks from premade libraries into a model window, connecting the blocks, and then setting or adjusting the preset dialog parameters.

The quantitative water management of the Charente River in France is a major policy concern because of freshwater scarcity in summer. In the context of the SPICOSA project (Science and Policy Integration for Coastal System Assessment) as mentioned below, this policy issue was chosen to apply the System Approach Framework (SAF) methodology. This led to modeling irrigation management strategies to quantify its impacts on various uses.

They built an external hydrological model in HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System) and interfaced with ExtendSim to work as a source of forcing. This strategy proved to be more efficient to model water shortages without renouncing the benefits of system-modeling inside the ExtendSim platform and with the advantage of a software dedicated to hydrological modeling. Using this experiment, the paper discusses the case of “in-line”, “on-line”, or “off-line” coupling modes to serve the objectives of policy orientated complex socio-ecosystems modeling.

This project contains a wealth of biomass feedstock information resources from the U.S. Department of Energy, Oak Ridge National Laboratory, Idaho National Laboratory, National Renewable Energy Laboratory, and other research organizations

This consortium used ExtendSim to create the Integrated Biomass Supply Analysis & Logistics (IBSAL) model. This biomass supply chain model starts from defining the logistical features of the supply such as number of farms involved, average yield, the start and progress of harvest schedule, and the moisture content of the crop.

The model also requires daily weather data such as temperature, relative humidity, wind speed, rainfall and snow fall. A spreadsheet containing equipment specifications provides data for calculating service times. This information is used in calculating drying and wetting of the biomass and workability of the soil. The user also defines the safe moisture content for baling and minimum temperature below which farm operations will cease. Once all input parameters are identified, the model calculates costs per ton of biomass, energy input and emissions (CO2) from equipment.

Stable, functional, and efficient bioethanol production systems on the national level must emphasize solutions of feedstock availability and transportation problems. Transportation logistics are a critical factor in the optimization of biomass supply chains. A single 25 million gallon per year cellulosic ethanol biorefinery will require delivery of 18,500 semi loads of bales to the plant. For a typical corn-stover biomass supply chain, baled corn stover must be transported in two phases, first from the field to a storage site and then from the storage site to the biorefinery. All activities between these two points are interconnected and together they form the biomass supply chain. The goal of supply-chain optimization is to minimize the total cost of these activities (transportation cost per unit, inventory cost per unit etc.) while satisfying the supply demands of a biorefinery.

A model of the supply-chain representing a realistic biomass transportation cycle between a single cornfield and biomass storage was created in ExtendSim. It included multiple simulations using different model factors providing a complete assessment of influence of various factors on system productivity.

A comprehensive middle school and high school environmental education program coupled with support from the National Science Foundation created an ExtendSim model simulating the effects of rainforest deforestation and agriculture (planting pasture crops) on the amount of CO2 in the atmosphere and on animals living in the rainforest. Hence, the Rainforest Carbon Cycling Model was born.

The Rainforest Carbon Cycling Model makes a tropical rain forest come alive as carbon from the air flows through it! Designed for users with no previous modeling experience, this model allows users to delve into ‘What if?’ sorts of questions about factors that limit forest production and the effects of land-use change on carbon cycling and global warming.

Rainforest Carbon Cycling Model History

Ann Russell, Terrestrial Ecosystems Ecologist at Iowa State University had a dream to develop a model of carbon cycling in a tropical rain forest using ExtendSim energy language model. Using data collected from research in a Costa Rican rainforest, Jim Dailey of Jim Dailey & Associates transformed the data into an animated, bilingual model for children and the general public and called it the Rainforest Carbon Cycling Model.

The model was distributed to 45,000 children in the Miami-Dade County school system through an outreach program organized by the Fairchild Tropical Botanical Gardens in Coral Gables, Florida called the Fairchild Challenge

Fairfield Challenge Overview

Designed for students of diverse interests, abilities, talents and backgrounds, the Fairchild Challenge is Fairchild Tropical Botanic Garden's environmental education outreach program. With separate but parallel programs for different grade levels 6 to 8 and 9 to 12, the Fairchild Challenge is composed of multidisciplinary competitions aligned with Sunshine State Standards.

The annual Fairchild Challenge options are intended to appeal to students' sense of play and creativity, to encourage them to experiment with ideas, projects and skills and to empower them to seek information and voice opinions. This free program was originally open to all schools in the greater Miami area. As of January 2010, 92 middle schools and 61 high schools are actively participating in the Fairfield Challenge. Other sites are replicating the Fairchild Challenge model nationally and abroad.

Simulation is used as a tool for describing visitor travel on the carriage roads of Acadia National Park, Maine, USA. The findings of this study suggest that computer simulation is useful for estimating current carrying capacity conditions, predicting future conditions, and guiding related research.

Using ExtendSim, the authors constructed a system model, MOSIM, that uses the physical reservoir data and minimum releases for hydropower and environmental constraints from a long-term study of the Missouri River basin. The value was based on the hydropower generated by the main-stem dams for a simulated period of 1898–1996 using MOSIM. Simulated forecasted flows were generated to represent the levels of predictability that had been determined in a previous study. The results demonstrate that use of climate forecast information along with better definition of the basin moisture states can improve runoff predictions with modest economic value that, in general, will increase as the size of the reservoir system decreases.

54 partner institutes in 21 countries used ExtendSim to study 18 coastal sites in the EU project SPICOSA. This project assisted Europe in its goal of achieving Sustainable Development by developing and testing a conceptual methodological framework for transition in coastal zones. The SPICOSA initiative originates from the fact that coastal systems are under increasing human pressure and policy had not been able to respond properly to the resulting negative impacts on ecological, social and economic systems.

SPICOSA´s overall aim was to develop a self-evolving, holistic research approach and support tools for the assessment of policy options for sustainable management through a balanced consideration of the ecological, social and economic aspects of Coastal Zone Systems (Integrated Coastal Zone Management).

All 18 study sites of SPICOSA used ExtendSim to describe a variety of coastal processes ranging from eutrophication, fisheries, and beach attractiveness to clam culture. They created a generic model library containing a complete set of reusable model components which were used to (re)build coastal models for new study areas, not much unlike the well-known Lego bricks.

The population of such a model library was one of the key challenges of the project and served several purposes:

• Existing models are easier to expand or maintain.
• New models were easier to build.
• Quick exchange of models within the scientific community.
• Avoidance of unnecessary modelling (not “reinventing the wheel”).

The principles of generic modelling were elaborated upon during the SPICOSA Cluster Workshops. For more information about ExtendSim use and its history in SPICOSA projects, read the series of newsletters on the SPICOSA site.

Developed in ExtendSim, the LIFE (Low Impact Feasibility Evaluation) model established functional connections between different land uses and landscape features. It has been used for:

• Design of volume or water quality based stormwater controls.
• Review of development/re-development plans for compliance with stormwater regulations.
• Incentive-based approaches such as environmental credit trading.
• Public education and outreach.