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Title: Dairy Analytics and Nutrient Analysis (DANA) Prototype System User Manual

Abstract

This document is a user manual for the Dairy Analytics and Nutrient Analysis (DANA) model. DANA provides an analysis of dairy anaerobic digestion technology and allows users to calculate biogas production, co-product valuation, capital costs, expenses, revenue and financial metrics, for user customizable scenarios, dairy and digester types. The model provides results for three anaerobic digester types; Covered Lagoons, Modified Plug Flow, and Complete Mix, and three main energy production technologies; electricity generation, renewable natural gas generation, and compressed natural gas generation. Additional options include different dairy types, bedding types, backend treatment type as well as numerous production, and economic parameters. DANA’s goal is to extend the National Market Value of Anaerobic Digester Products analysis (informa economics, 2012; Innovation Center, 2011) to include a greater and more flexible set of regional digester scenarios and to provide a modular framework for creation of a tool to support farmer and investor needs. Users can set up scenarios from combinations of existing parameters or add new parameters, run the model and view a variety of reports, charts and tables that are automatically produced and delivered over the web interface. DANA is based in the INL’s analysis architecture entitled Generalized Environment for Modeling Systemsmore » (GEMS) , which offers extensive collaboration, analysis, and integration opportunities and greatly speeds the ability construct highly scalable web delivered user-oriented decision tools. DANA’s approach uses server-based data processing and web-based user interfaces, rather a client-based spreadsheet approach. This offers a number of benefits over the client-based approach. Server processing and storage can scale up to handle a very large number of scenarios, so that analysis of county, even field level, across the whole U.S., can be performed. Server based databases allow dairy and digester parameters be held and managed in a single managed data repository, while allows users to customize standard values and perform individual analysis. Server-based calculations can be easily extended, versions and upgrades managed, and any changes are immediately available to all users. This user manual describes how to use and/or modify input database tables, run DANA, view and modify reports.« less

Authors:
;
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1070144
Report Number(s):
INL/EXT-12-27658
DOE Contract Number:  
DE-AC07-05ID14517
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; Dairy Anaerobic Digestion; Dairy Biogass

Citation Formats

Alessi, Sam, and Keiser, Dennis. Dairy Analytics and Nutrient Analysis (DANA) Prototype System User Manual. United States: N. p., 2012. Web. doi:10.2172/1070144.
Alessi, Sam, & Keiser, Dennis. Dairy Analytics and Nutrient Analysis (DANA) Prototype System User Manual. United States. https://doi.org/10.2172/1070144
Alessi, Sam, and Keiser, Dennis. 2012. "Dairy Analytics and Nutrient Analysis (DANA) Prototype System User Manual". United States. https://doi.org/10.2172/1070144. https://www.osti.gov/servlets/purl/1070144.
@article{osti_1070144,
title = {Dairy Analytics and Nutrient Analysis (DANA) Prototype System User Manual},
author = {Alessi, Sam and Keiser, Dennis},
abstractNote = {This document is a user manual for the Dairy Analytics and Nutrient Analysis (DANA) model. DANA provides an analysis of dairy anaerobic digestion technology and allows users to calculate biogas production, co-product valuation, capital costs, expenses, revenue and financial metrics, for user customizable scenarios, dairy and digester types. The model provides results for three anaerobic digester types; Covered Lagoons, Modified Plug Flow, and Complete Mix, and three main energy production technologies; electricity generation, renewable natural gas generation, and compressed natural gas generation. Additional options include different dairy types, bedding types, backend treatment type as well as numerous production, and economic parameters. DANA’s goal is to extend the National Market Value of Anaerobic Digester Products analysis (informa economics, 2012; Innovation Center, 2011) to include a greater and more flexible set of regional digester scenarios and to provide a modular framework for creation of a tool to support farmer and investor needs. Users can set up scenarios from combinations of existing parameters or add new parameters, run the model and view a variety of reports, charts and tables that are automatically produced and delivered over the web interface. DANA is based in the INL’s analysis architecture entitled Generalized Environment for Modeling Systems (GEMS) , which offers extensive collaboration, analysis, and integration opportunities and greatly speeds the ability construct highly scalable web delivered user-oriented decision tools. DANA’s approach uses server-based data processing and web-based user interfaces, rather a client-based spreadsheet approach. This offers a number of benefits over the client-based approach. Server processing and storage can scale up to handle a very large number of scenarios, so that analysis of county, even field level, across the whole U.S., can be performed. Server based databases allow dairy and digester parameters be held and managed in a single managed data repository, while allows users to customize standard values and perform individual analysis. Server-based calculations can be easily extended, versions and upgrades managed, and any changes are immediately available to all users. This user manual describes how to use and/or modify input database tables, run DANA, view and modify reports.},
doi = {10.2172/1070144},
url = {https://www.osti.gov/biblio/1070144}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Oct 01 00:00:00 EDT 2012},
month = {Mon Oct 01 00:00:00 EDT 2012}
}