# Application of Variance-Based Sensitivity Analysis to a Large System Dynamics Model

## Abstract

Variance-based sensitivity methods can provide insights into large computational models. We present a novel application of sensitivity analysis to the Biomass Scenario Model (BSM) a large and complex system dynamics model of the developing biofuels industry in the United States. We apply a two-stage sensitivity approach consisting of an initial sensitivity screening, followed by a variance decomposition approach. Identifying key system levers and quantifying their strength is not straightforward in complex system dynamics models that have numerous feedbacks and nonlinear results. Variance-based sensitivity analysis (VBSA) offers a systematic, global approach to assessing system dynamics models because it addresses nonlinear responses and interactive effects. Especially when a large model's size makes manual exploration of the input space difficult and time-consuming, the approach can help to provide a comprehensive understanding of interactions that drive model behaviors.

- Authors:

- National Renewable Energy Laboratory (NREL), Golden, CO (United States)

- Publication Date:

- Research Org.:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)

- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Bioenergy Technologies Office (EE-3B)

- OSTI Identifier:
- 1468525

- Report Number(s):
- NREL/JA-6A20-70809

- DOE Contract Number:
- AC36-08GO28308

- Resource Type:
- Journal Article

- Journal Name:
- Cornell University Library Preprint Archive

- Additional Journal Information:
- Journal Name: Cornell University Library Preprint Archive

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 97 MATHEMATICS AND COMPUTING; variance based sensitivity analysis; statistical programming; R statistical programming language; biofuel; biomass; system dynamics

### Citation Formats

```
Inman, Daniel J, Vimmerstedt, Laura J, Bush, Brian W, Stright, Dana K, and Peterson, Steve.
```*Application of Variance-Based Sensitivity Analysis to a Large System Dynamics Model*. United States: N. p., 2018.
Web.

```
Inman, Daniel J, Vimmerstedt, Laura J, Bush, Brian W, Stright, Dana K, & Peterson, Steve.
```*Application of Variance-Based Sensitivity Analysis to a Large System Dynamics Model*. United States.

```
Inman, Daniel J, Vimmerstedt, Laura J, Bush, Brian W, Stright, Dana K, and Peterson, Steve. Wed .
"Application of Variance-Based Sensitivity Analysis to a Large System Dynamics Model". United States.
```

```
@article{osti_1468525,
```

title = {Application of Variance-Based Sensitivity Analysis to a Large System Dynamics Model},

author = {Inman, Daniel J and Vimmerstedt, Laura J and Bush, Brian W and Stright, Dana K and Peterson, Steve},

abstractNote = {Variance-based sensitivity methods can provide insights into large computational models. We present a novel application of sensitivity analysis to the Biomass Scenario Model (BSM) a large and complex system dynamics model of the developing biofuels industry in the United States. We apply a two-stage sensitivity approach consisting of an initial sensitivity screening, followed by a variance decomposition approach. Identifying key system levers and quantifying their strength is not straightforward in complex system dynamics models that have numerous feedbacks and nonlinear results. Variance-based sensitivity analysis (VBSA) offers a systematic, global approach to assessing system dynamics models because it addresses nonlinear responses and interactive effects. Especially when a large model's size makes manual exploration of the input space difficult and time-consuming, the approach can help to provide a comprehensive understanding of interactions that drive model behaviors.},

doi = {},

journal = {Cornell University Library Preprint Archive},

number = ,

volume = ,

place = {United States},

year = {2018},

month = {3}

}