4 Project Information
4.6 Technology Readiness ASSESSMENT
4.6.1 Performance Level of the Completed Work
This project involved twelve different tasks, each of which were mapped to a specific Technology Readiness Level (TRL). The Technology Readiness Levels specific to each project Task of the research are listed in Table 7. A summary of the interrelationships of the tasks is shown in Figure 2.
TABLE 7. TECHNOLOGY READINESS LEVEL FOR EACH PROJECT TASK
Technology Readiness Level Task in Project1 Description Level 1 – Basic Principles
Observed and Reported Task 1 – Establishment of an Advisory Group
Task 2 – Select Water Utility Partners
Initiate project and refine scope of work
Work with the advisory group to identify three utilities to partner in the project Level 2 – Technology concept
and Application Formulation Task 3 – Survey SCADA systems for use in water distribution systems and
Level 3 – Analytical and Experimental Critical Function and Characteristic Proof of Concept
Task 4 – Build laboratory scale hydraulic model of selected water distribution system (medium utility)
Task 5 – Develop Graphical Flow Dynamics Model
Construct physical model of skeletonized water distribution network in UK hydraulic laboratory. Use the model to simulate the flow conditions of the actual system.
Develop a graphical user interface which will allow utilities to build a graphical schematic of their distribution system using pre-existing GIS data to display the flow
distribution across the network for a given set of operational conditions. Apply the model to each of the systems of the selected utility partners.
Level 4 – Component or breadboard validation in laboratory environment
Task 6 – Develop and calibrate hydraulic and water quality models for small and medium sized utilities respectively.
Develop and calibrate
hydraulic models of a small and medium sized water utility in order to identify data quality requirements and to develop
44 | P a g e Technology Readiness Level Task in Project1 Description
Task 7 – Evaluate Real-Time Model Using Historic SCADA Data
Task 8 – Develop Sensor Placement Guidance
data collection protocols.
Develop and calibrate water quality model of a medium sized water utility in order to identify data quality
requirements and to develop data collection protocols.
Develop laboratory scale model of a medium sized utility water distribution system and
evaluate the reliability of existing hydraulic and water quality software.
Test the efficacy and resiliency of the real-time
hydraulic/water quality model using historic SCADA data from the large system utility partner in order to determine the sensitivity of water quality predictions to network flow dynamics.
Develop guidance for optimal placement of flow and pressure sensors based on results of flow dynamics model and operational constraints of the utility. Use the guidance to recommend hydraulic and water quality sensor placement for the small and medium sized utility respectively.
Level 5 – Component or breadboard validation in relevant environment
Task 9 – Develop Toolkit Develop a decision-making toolkit which will allow utilities to select the appropriate level of operational tools in support of their operational needs.
Level 6 – System model or prototype demonstration in a relevant environment
Task 10 – Test and Evaluate Toolkit
Task 11 – Test and validate Toolkit
Test the efficacy and resiliency of the toolkit prototype with each of the three utility partners.
Conduct one day workshop with selected utilities to validate the toolkit
45 | P a g e Technology Readiness Level Task in Project1 Description
Task 12 – Write Report Synthesize and summarize the results of these research efforts.
1Detailed descriptions of the Project Tasks are provided in Section 4.2 4.6.2 REQUIREMENTS TO ACHIEVE TRL 9
This research ended at Technology Readiness Level 6 with the testing and evaluation of a prototype toolkit in both simulated and controlled environments. The toolkit allows utilities to select the appropriate level of technology in support of their operational needs and provides guidance with regard to sensor placement and emergency response. The estimated work required to achieve Technology Readiness Level 9 includes:
TRL 7 Distribute toolkit and graphical flow distribution software to selected utilities (e.g. with smaller sized water distribution systems). Use graphical flow distribution software to generate computerized schematics of selected water distribution systems along with flow distribution realizations. Use toolkit to assist in the placement of additional hydraulic monitoring sensors in support of normal operations and the development of a baseline hydraulic model. This objective is currently being pursued through a partnership between the University of Kentucky, KYPIPE, and several smaller water utilities in Kentucky (e.g. Paris Kentucky) as well as the KY/TN AWWA and the KSWOA.
TRL 8 Use the operational toolkit to facilitate upgrading of operational technologies of selected water utilizes (e.g. with medium size water distribution systems). Such operational technologies would include water quality models of the distribution systems along with an operational SCADA system that supports both hydraulic and water quality sensors. This objective is currently being pursued through a partnership between the University of Kentucky, KYPIPE, and several medium water utilities in Kentucky (e.g. Nicholasville, Kentucky) and through Open Engineering, LLC, and several medium size water utilities in Alabama.
TRL 9 Use the operational toolkit to facilitate the upgrading of the operational technologies of selected water utilities (e.g. with larger distribution systems) to support integration of a SCADA database with real time water distribution models (both hydraulic and water quality) for use in supporting normal system operations as well as detection of water quality anomalies that may be caused by accidental or intentional contamination incidents. This objective is currently being pursued through a partnership with CitiLogics, LLC, and several larger water distribution systems across the United States (e.g. Northern Kentucky Water District).
5 COMMERCIALIZATION PLAN
This research effort has produced several potential commercial products:
1. A graphical flow model
2. A water quality sensor location tool
3. Water Wizard - an expert system based operational guidance tool
46 | P a g e 4. EPANET-RTX
5. Water Distribution System Toolkit
The graphical flow model (i.e. GFM) and the water quality sensor location tool are both currently being marketed by KYPIPE, LLC. Water Wizard is currently being marketed through a partnership with Open Engineering, LLC. EPANET-RTX is being marketed through a partnership with CitiLogics, LLC, which also provides consulting services to those water utilities desiring to use real-time analytics and real-time modeling in support of their system operations. The Water Distribution System Toolkit, is currently being maintained by the University of Kentucky Water Resources Research Institute, with no current plans to commercialize the site.
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6 REFERENCES
1. Aditya Tadakaluru, Karla M. Andrew, Mostafa Mostafa, and Andrew Ernest. 2005.
"GeoExpert A Framework for Data Quality in Spatial Databases" CIMCA/IAWTIC 2: 557-561.
2. Allgeier, et al, 2008. Proceedings of the American Water Works Association's Water Quality Technology Conference, Cincinnati Ohio, November.
3. Andrew, K, Tope S, Ernest ANS, Lyon J. 2005. Utilizing Integrated-GIS to Combat Bioterrorist Threats & Protect Drinking Water. Kentucky GIS Conference.
4. ASCE. 2009. Report Card for America’s Infrastructure. Reston, Virginia. 168 pp. March 25, 2009.
5. BOSC. 2008. “Review of the U.S. Environmental Protection Agency, Office of Research and Development’s Homeland Security Research Program, Board of Scientific Counselors, Subcommittee on Homeland Security Research Program, http://www.epa.gov/osp/bosc.
6. Buchberger, S.G., J.T. Carter, Y. H. Lee, and T. G. Schade, “Random Demands, Travel times, and Water Quality in Deadends.” AwwaRF/AWWA, Denver, CO, 2003.
7. Buchberger, S., Clark, R., Grayman, W., Li, Z., McCutcheon, M., and Yang, J. 2009. “Needs and Trends of the Nation’s Water Infrastructure – The Utility Perspective.” Proceedings of the World Environmental and Water Resources Congress, Kansas City, Kansas, May 18-22, 2009.
8. Chang, N. B., Ernest, A., and Makkeasorn, A., 2007. "Rule-based Expert System for Sensor Deployment in Drinking Water Systems for Rural Communities," 6th International Conference on Environmental Informatics, November 21-23, 2007, Bangkok, Thailand, oral presentation.
9. Dietrich, Jens. 2003. The Madarax 3.0 Manual. Institute of Information Sciences and Technology, Massey University, New Zealand.
10. Ernest, A. N. S., 2006a "Long Term Control Plan Development for Small Communities Utilizing an Online Expert System", Proceedings of the 5th International Conference on Environmental Informatics, Bowling Green, Kentucky, International Society for Environmental Information Sciences.
11. Ernest, A.N.S. 2006b. GIS Integrated Expert System for Stormwater Management. Kentucky MS4 Workshop
12. Ernest, A.N.S., Fattic, J., Andrew, K., Ballweber, J., Chang, N.B., Fowler, R. 2009a. Water Resource Management Capacity Development: A Small-Systems Technology-Transfer Model, Proceedings of the Annual Conference & Exposition, American Society for Engineering Education, Austin, Texas, June 14-17.
13. Ernest, A.N.S., Andrew, K., Chang, N.B., Makkeasorn, A., Fan, Y. 2009b. Improving Local Water Supply in Rural Communities via a Sensor Network, Fifth Kentucky Innovation and Entrepreneurship Conference (KIEC), Louisville, Kentucky, April 7.
14. Fencil, J., “Lessons learned from Drills and Exercises at the Greater Cincinnati Water works World Environmental and Water Resources Congress, May 18, 2010, Providence, R.I.
15. Friedman-Hill, E. 2007. JESS, the Rule Engine for the Java Platform.
16. Hart, D.B., and McKenna, S.A., 2009. CANARY User’s Manual Version 4.1.L
17. Irving, J., Taggart, T., Reilly, B, Spangler, L., 2010. “CANARY – Philadelphia Water Department’s Investigation into using CANARY to monitor OWQM Sites,” World Environmental and Water Resources Congress, May 18, 2010, Providence, R.I.
18. Lee, Y. 2004. Mass Dispersion in Intermittent Laminar Flow. Ph.D. Dissertation in Civil and Environmental Engineering, University of Cincinnati, Cincinnati, Ohio.
48 | P a g e 19. Lee, Y. and S. G. Buchberger. 2001. “Estimation of dispersion in unsteady random flow
conditions in dead-end pipes of water distribution systems,: Proceedings, ASCE-EWRI World Water & Environmental Resources Congress, Orlando, FL..
20. NRC, 2005. “Public Water Distribution Systems, Assessing and Reducing Risks,” First Report, Committee on Public Water Supply Distribution Systems: Assessing and Reducing Risks, Water Science and Technology Board, National Research Council of the National Academies, The National Academies Press, Washington, DC.
21. NRC, 2006a. “Facing Hazards and Disasters: Understanding Human Dimensions,” Committee on Disaster Research in the Social Sciences: Future Challenges and Opportunities, Division on Earth and Life Studies, National Research Council of the National Academies, The National Academies Press, Washington, DC.
22. NRC, 2006b. Drinking Water Distribution Systems: Assessing and Reducing Risks, Committee on Public Water Supply Distribution Systems: Assessing and Reducing Risks, Water Science and Technology Board, National Research Council of the National Academies, The National Academies Press, Washington, DC.
23. NRC, 2007. Improving the Nation’s Water Security: Opportunities for Research, Committee on Water System Security Research, Water Science and Technology Board, National Research Council of the National Academies, The National Academies Press, Washington, DC.
24. Ormsbee, L, 2006. “The History of Water Distribution Modeling,” Proceedings of the ASCE Water Distribution Specialty Conference, Cincinnati, Ohio, August 2-7.
25. Pickard, Brian, 2010. “Overview of the U.S. EPA Water Security Initiative, World Environmental and Water Resources Congress, May 18, 2010, Providence, R.I.
26. Tadakaluru, A, Andrew K, Mostafa M, Ernest ANS. 2005. GeoExpert A Framework for Data Quality in Spatial Databases: 557-561.
27. Tzatchkov, V. G., A.A. Aldama, and F.I. Arreguin. 2002. Advection-dispersion Reaction Modeling in Water Distribution Networks.” Journal Water Resources Planning &
Management, 128(5): 334-342.
28. US EPA. 2002. The Clean Water and Drinking Water Infrastructure Gap Analysis, EPA 816-R-02-020, Office of Water, September, 54 pp.
29. US EPA. 2005. Water Distribution System Analysis: Field Studies, Modeling and Management – A Reference Guide for Utilities, EPA/600/R-06/028, Cincinnati, Ohio.
30. US EPA. 2009. CANARY User’s Manual Version 4.1, National Security Applications Dept., Sandia National Laboratories, Albuquerque, NM 87185-0735.
31. Van Bloemen Waanders, B., B. G. Hammond, J. Shadid, S. Collis, and R. Murray. 2005. “A comparison of Navier-Stokes and Network Models to predict Chemical Transport in Chemical Transport in Municipal Water Distribution Systems.” Proceedings , ASCE –EWRI World Water and Environmental Resources Congress, Anchorage, AK.
32. Wood, Reddy, L., Funk, J., (1993. “Modeling Pipe Networks Dominated by Junctions.” ASCE Journal of Hydraulic Engineering, August, 1993.Wood, Reddy, L., Funk, J., 1993.
33. Wood, Reddy, L., Funk, J., (1994) “Incorporating Flow Dependent Loss Coefficients into Pipe Network Models,” Integrated Computer Applications in Water Supply: Methods and Procedures for System Simulation and Control (Vol 1). Wiley and Sons, New York, NY: 19-34.
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7 ACRONYMS
ASCE – American Society of Civil Engineers
AMWA – The Association of Metropolitan Water Agencies (http://www.amwa.net/) ATSDR – Agency for Toxic Substances and Disease Registry
AWWA – American Water Works Association (http://www.awwa.org) BOSC – Board of Scientific Counselors
CIP – Critical Infrastructure Protection CWA – Clean Water Act
CWS – Contaminant Warning System DHS – Department of Homeland Security EPA – Environmental Protection Agency
EWRI – Environmental and Water Resources Institute GFM – Graphical Flow Model
HSPD - Homeland Security Presidential Directives KAWC – Kentucky American Water Company KCI – Kentucky Critical Infrastructure
KDOW – Kentucky Division of Water
KWRRI – Kentucky Water Resources Research Institute LWC – Louisville Water Company
MWH – Montgomery Watson Harza
NAWC – The National Association of Water Companies (http://www.nawr.org/index.html) NHSRC - National Homeland Security Research Center
NIEHS - National Institute of Environmental Health Sciences NIHS – National Institute of Hometown Security
NKWD – Northern Kentucky Water District
NOAA – National Oceanic and Atmospheric Administration NPDES – National Pollutant Discharge Elimination System
50 | P a g e NRC – National Research Council
NRWA – National Rural Water Association (http://www.nrwa.org/) PLC – Programmable Logic Controller
QAPP – Quality Assurance Project Plan RFP – Request for Proposals
RTU – Remote Terminal Unit SPOT – Sensor Placement Software
SCADA – Supervisory Control and Data Acquisition SDWA – Safe Drinking Water Act
TEVA – Threat Ensemble Vulnerability Assessment UC – University of Cincinnati
UM – University of Missouri UK – University of Kentucky WDS – Water Distribution System
WDST – Water Distribution System Toolkit WKU – Western Kentucky University WQMS - Water Quality Monitoring System
8 MAJOR NETWORK ANALYSIS SOFTWARE
EPANET (http://www.epa.gov/nrmrl/wswrd/dw/epanet.html) Haestad Methods (http://www.haestad.com/)
KYPIPE (http://www.KYPIPE.com/home.html) MWH Soft (http://www.mwhsoft.com/)
http://www.bentley.com/en-US/Products/WaterGEMS/SCADAConnect-Overview.htm
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9 APPENDICES
9.1 APPENDIX A: DHS TECHNOLOGY READINESS LEVELS
Program
Type Level TRL Description
Basic
Research 1 Basic principles observed and reported
Lowest level of technology readiness. Scientific research begins to be translated into technologies' basic properties.
2 Technology concept and/or application formulated
Invention begins. Once basic principles are observed, practical applications can be invented. The application is speculative and there is no proof or detailed analysis to support the assumption. Examples are still limited to paper studies.
Active R&D is initiated. This includes analytical studies and laboratory studies to physically validate analytical predictions of separate elements of the technology. Examples include components that are not yet integrated or representative.
Applied
Research 4 Component and/or breadboard validation in laboratory
environment
Basic technological components are integrated to establish that the pieces will work together. This is relatively "low fidelity" compared to the eventual system. Examples include integration of ad hoc hardware in a laboratory.
5 Component and/or breadboard validation in relevant
environment
Fidelity of breadboard technology increases significantly. The basic technological components are integrated with
reasonably realistic supporting elements so that the
technology can be tested in simulated environment. Examples include "high fidelity" laboratory integration of components.
6 System/subsystem model or prototype demonstration in a relevant environment
Representative model or prototype system, which is well beyond the breadboard tested for level 5, is tested in a relevant environment. Represents a major step up in technology's demonstrated readiness. Examples include testing a prototype in a high fidelity laboratory environment or in a simulated operational environment
Advanced
Technology 7 System prototype demonstration in an operational
environment
Prototype near or at planned operational system. Represents a major step up from level 6, requiring demonstration of an actual system prototype in an operational environment.
Examples include testing the prototype in a test bed.
8 Actual system completed and qualified through test and demonstration
Technology has been proven to work in its final form and under expected conditions. In almost all cases, this level represents the end of true system development. Examples include developmental test and evaluation and evaluation to determine if it meets design specifications.
9 Actual system proven through successful mission operations
Actual application of the technology in its final form and under mission conditions, such as those encountered in operational test and evaluation. Examples include using the system under operational mission conditions.
NIHS RFP – Hydraulic Modeling March 31, 2009
52 | P a g e 9.2 APPENDIX B: ORIGINAL REQUEST FOR PROPOSAL
The National Institute for Hometown Security Request for Proposal
Studying Distribution System Hydraulics and Flow Dynamics to Improve Water Utility Operational Decision Making
Kentucky Critical Infrastructure Protection Program
Solicitation Based on Department of Homeland Security Capability Gap Statement 2008-004-Water: “Hydraulic Modeling”
April 2009
NIHS RFP – Hydraulic Modeling March 31, 2009
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Table of Contents
1.0 Introduction 54 2.0 Objective 54 3.0 Capability Gap 54 3.1 Threat Identification 54
3.2 Gap Statement 54 3.3 Research Framework 54 3.4 Development Considerations 55 4.0 Possible Approach 55
4.1 Baseline Recommendations for Implementation 56 5.0 Goal and Desired Outcomes 57
5.1 Deliverables 57 6.0 Evaluation Criteria 57 7.0 Proposal Submission 58 7.1 Proposal Format 58
7.2 Response Deadline and Submission Requirement 58 8.0 References 59
NIHS RFP – Hydraulic Modeling March 31, 2009
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1.0 Introduction
The National Institute for Hometown Security (NIHS or the Institute) was formed in 2004 to assist the U.S. Department of Homeland Security (DHS) Science and Technology Directorate (S&T) in creating and delivering new and innovative technologies to address the nation’s community-based critical infrastructure challenges. NIHS is tasked by DHS S&T to manage the Kentucky Critical Infrastructure Protection (KCI) program which focuses on research, development, and transition-to-use of technologies designed for community, state, and regional applications.
Technologies developed under this program are defined by a user-driven needs and requirements process. A “need” is a mission-oriented capability gap within an operational context (e.g., a new threat environment is at risk for exposure to chemical agents; the emergency response community will therefore need solutions to detect and define the chemicals to both prevent unnecessary exposure and, should exposure occur, to ensure the most appropriate remedial action is taken in a timely manner). “Requirements” are the functional specifications associated with a technology solution (e.g., “the chemical detector will have a false-positive rate of less than 5%, a range of 100 meters, include both visual and audio alarms, and be able to detect blood, blister, choking, and nerve agents”). To enable the development and eventual deployment of critical infrastructure protection (CIP) technology solutions, NIHS has worked with DHS to identify and define the actionable requirements presented in this solicitation based upon user needs.
Needs identification is a function of the annual KCI project proposal and awards process. S&T and NIHS receive a vetted list of sector-specific prioritized needs from DHS Office of Infrastructure Protection (IP) and then distill them into highly specific requirements used for KCI request for proposals (RFPs). When this task is complete, NIHS prepares the RFPs and solicits, awards, and manages the contracts that fill the identified gaps. RFPs are disseminated to the Kentucky Homeland Security University Consortium, and participation by other universities and private industry stakeholders is encouraged where appropriate.
This solicitation is in response to capability gap statement “2008-004-Water: Hydraulic Modeling,” identified by DHS IP as a critical need for the Water Sector.
2.0 Objective
Despite advances in the modeling of water quality in water distribution systems and in the more sophisticated area of sensor placement, many questions remain about the flow dynamics and system hydraulics of water distribution systems. The objective of this project is to enhance understanding of flow dynamics and system hydraulics in community water systems in order to improve water utility operational decision making from event detection to system recovery.
Since water chemistry depends on flow, this work can also be useful to people doing real-time
water quality monitoring and to enhance research activities being directed at event detection
systems and real-time modeling.
NIHS RFP – Hydraulic Modeling March 31, 2009
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3.0 Capability Gap
3.1 Threat Identification
Water quality changes can arise because of a malevolent threat or as a result of operational and hydraulic changes that impact water quality parameters. Proper interpretation of distribution system water quality data and the ability to respond effectively to unanticipated changes in water quality parameters depends on an understanding and consideration of flow dynamics occurring within the system. It is important to detect events as early as possible and understand how flow dynamics can affect water quality causing an impact on the operation of distribution system monitoring systems.
3.2 Gap Statement
The Water Sector Research and Development Working Group has stated that water utilities would benefit from a clearer and more consistent understanding of their system flow dynamics.
Understanding flow dynamics is important to interpreting water quality measurements and to inform basic operational decision making of the water utility.
Water quality changes may be predictably associated with normal operational flow patterns within the distribution system or changes in flows from the operation of pumps, hydrants, or as a result of
Water quality changes may be predictably associated with normal operational flow patterns within the distribution system or changes in flows from the operation of pumps, hydrants, or as a result of