Sunil K Sinha is a/an Professor in the University Of California department at University Of California
Virginia Tech - Civil Engineering
Penn State University
State College
Pennsylvania
Research
Teaching
and Consulting in the areas of infrsatructure system
Assistant Professor
Penn State University
Professor of Civil and Environmental Engineering and Director of Sustainable Water Infrastructure Management (SWIM) Center at Virginia Tech.\nResearch
Teaching
and Consulting are in the areas of asset management
pattern recognition
sensor informatics
sustainable and resilient infrastructure
especially drinking water
wastewater
and stormwater infrastructure systems.
Virginia Tech
Post-Doctoral Fellowship
Natural Sciences & Engineering Research Council (NSERC)
Canada
CAREER Award titled “Sustainable Water Infrastructure Management System (SWIMS)
National Science Foundation (NSF)
College of Engineering Faculty Fellow
Virginia Tech
Schreyer Institute InSPIRE Academy Fellow
Penn State
Liquid Assets: The Story of Our Water Infrastructure has been awarded the Engineering Journalism Award
American Association of Engineering Societies
International Research and Education in Engineering (IREE) Award
National Science Foundation (NSF)
PhD Dual Degree
Dissertation Topic: Automated Pipeline Condition Assessment Using Advanced Computer Vision
Civil Engineering and Systems Engineering
CSCE
NASTT
University of Waterloo
M.A.Sc.
Thesis Topic: An Artificial Neural Network Approach to Predict Organizational Effectiveness
Master of Applied Science in Civil Engineering
Project Management
University of Waterloo
The World Bank
Environmental impact analysis of infrastructure projects
The World Bank
Bachelor of Engineering (BE)
Civil Engineering
Photographic
BIT MESRA
The Utility Infrastructure Asset Management (UIAM) Division will advance and disseminate knowledge related to the holistic life-cycle asset management of utility infrastructure that will assure resiliency and sustainability. This Division will support the goal of UTILITY ENGINEERING AND SURVEYING INSTITUTE (UESI) to provide leadership to utilities for effectively managing their systems to be reliable
resilient and sustainable. UIAM will provide expert leadership that will support the development of ASCE’s American Infrastructure Report Card.
American Society of Civil Engineers
Vice-Chair - Water Sector Systems Resilience Standing Committee
Recent floods
tornadoes
and earthquakes remind us that natural
technological
and human-caused hazards take a high toll on communities. Costs in lives
livelihoods and quality of life can be reduced by better managing disaster risks. We can strengthen resilience and improve a community's ability to maintain and restore vital services in a more timely way and to build back better.\n\nTo address this challenge
NIST manages a multi-faceted program
assisting communities and stakeholders on issues related to buildings and the interdependencies of physical infrastructure systems. The Community Resilience Program
part of NIST's broader disaster resilience work
complements efforts by others in the public and private sectors.\n
National Institute of Standards and Technology
Stormwater Management
Water Resources
Modeling
Environmental Awareness
GIS
Water Quality
Matlab
Sustainability
ArcGIS
Computer Vision
Engineering
Numerical Analysis
Structural Analysis
Environmental Engineering
Water
Mathematical Modeling
Hydrology
Geotechnical Engineering
Wastewater Treatment
Civil Engineering
A Validation and Verification Framework for Robust Drinking Water Pipeline Model Prediction Models
Many models are used to evaluate and predict risk analysis
as well as renewal prioritization
of drinking water and wastewater pipelines. The majority have not been accurate enough to be used for real decision making applications. This paper proposes a model framework for asset management programs with two major stages; verification and validation. The verification stage confirms that there are no errors in the code or logic in the model’s algorithm. Two approaches make up the models’ verification framework--tests with artificial data and tests with field data. The second stage of the proposed framework validates that the model goes through three steps: lab tests
expert opinions and model’s outputs. Evaluation results were compared to confirm the model’s accuracy. This framework is precise enough to prove the correctness and accuracy of many different types of models created for decision support for asset management of drinking water pipelines.\n
A Validation and Verification Framework for Robust Drinking Water Pipeline Model Prediction Models
This paper presents a methodology for developing a national database
as applied to water infrastructure systems that include both drinking water and wastewater. The database is branded as WATERiD and can be accessed through internet.
Development of a Water Infrastructure Knowledge Database
The practices from water and wastewater utilities were determined by the help of participation utilities to the WATERiD Database. Case studies in locating technology applications and locating practice application was written to capture these practices. These case studies were also supplemented by phone interviews with various utilities. Comparison between the literature and utility practice indicated various gaps in the utility practice. Recommendations are offered to fill these gaps for an effective use of underground utility practices by water and wastewater utilities. These recommendation include adaptation and implementation of specific best practices of transportation industry by the water and wastewater utilities.
Underground Utility Locating Technology (INFR9SG09/INFR10SG09UULT)
Development of a Fuzzy Inference Performance Index for Water Pipe
The primary objective of this paper is to develop a fuzzy inference performance index for metallic drinking water pipelines. Evaluation of the performance index is accomplished through testing of artificial
field
and lab data.
Development of a Fuzzy Inference Performance Index for Water Pipe
This paper presents a standard data structure for predicting the remaining physical life and consequence of failure of water pipes. Correlating the various pipe material types with the pipe life cycle
failure modes and mechanisms are crucial in defining the various parameters.
Standard Data Structure for Predicting the Life and Consequence of Failure of Water Pipes
This paper focuses on the development of a web-based geospatial tool as a proof of concept to assist water utilities in performing a network-level risk screening of their buried pipeline infrastructure systems. This tool provides a preliminary risk screening at a high level to quickly identify problematic (hot spot) areas and help guide decisions about where to further analyze pipeline infrastructure.
Web-Based and Geospatially Enabled Risk Screening Tool for Water Pipeline
The objective of this research is to analyze the capabilities and limitations of current condition assessment technologies and performance prediction methods and to propose direction for future research on PCCP by considering its failure factors
modes
and mechanisms.
Failure Analysis
Condition Assessment Technologies
and Performance Prediction of Prestressed-Concrete Cylinder Pipe
The proposed performance-rating system evaluates each parameter and combines them mathematically through a weighted summation and a fuzzy inference system that reflects the importance of the various factors. The framework provides a noticeable improvement from the conventional practice of using solely inspection data as a means to evaluate wastewater pipe.
Development of a Robust Wastewater Pipe Performance Index
The practices from water and wastewater utilities were determined by the help of participation utilities to the WATERiD Database. Case studies in locating technology applications and locating practice application was written to capture these practices. These case studies were also supplemented by phone interviews with various utilities. Comparison between the literature and utility practice indicated various gaps in the utility practice. Recommendations are offered to fill these gaps for an effective use of underground utility practices by water and wastewater utilities. These recommendation include adaptation and implementation of specific best practices of transportation industry by the water and wastewater utilities.
Underground Utility Locating Technology (INFR9SG09/INFR10SG09UULT)
Stochastic Simulation Methodology for Resilience Assessment of Water Distribution Networks
This paper presents a novel network-based methodology to evaluate resilience of water distribution systems. This methodology utilises stochastic simulation on a network model to generate statistical data on the resilience probability of the actual water infrastructure system. The methodology is a management decision support tool for enhancing system preparedness.
Stochastic Simulation Methodology for Resilience Assessment of Water Distribution Networks
A comprehensive approach to managing our capital assets is overdue - one that brings \"state of the practice\" advanced asset management (AM) concepts
tools
techniques
and technologies to bear on managing for cost-effective performance. This approach is one that focuses relentlessly on providing sustained performance to the customer at the lowest life-cycle cost and at an acceptable level of risk to the organization. - See more at: http://www.cpe.vt.edu/swim/workshop/index.html#sthash.RyFNSIi1.dpuf
Richard Thomasson
Sustainable Water Infrastructure Management (SWIM) Center at Virginia Tech
VISION\nTo become the premier global knowledge and resource organization for planning
engineering
constructing\nand operating sustainable and resilient water infrastructure systems.\nMISSION\nTo bring together the global water industry to improve the performance
sustainability
and resiliency of\nexisting and future water infrastructure systems.\nCORE ACTIVITIES\n• Promote a collaborative environment within the water infrastructure community and disseminate critical\ninformation to improve performance
sustainability
and resiliency\n• Create and share water infrastructure data
analytical tools and techniques
best practices
\ncase studies and synthesis reports\n• Foster multidisciplinary collaboration among water experts to advance and shape water infrastructure\nindustry\n• Advance science and technology through leading-edge innovative research and\ninterdisciplinary education\n• Articulate priorities for global water infrastructure systems and promote interactions among\ndiverse water utilities\n• Develop and deliver the most comprehensive source of water infrastructure asset management information\nand innovative research available through WATERiD and PIPEiD national databases
conferences
workshops
\ntraining courses
publications
reports
and online certification programs\n• Pioneer outreach programs that are renowned for addressing local
state
national
\nand international water infrastructure asset management challenges
Dave Fletcher
Mike Burkhard
Pipeline Infrastructure Database (PIPEiD)
PIPEiD is envisioned to be “a Living Database Platform for Advanced Asset Management” addressing all three major management levels including strategic
tactical
and operational that will assist water utilities of all sizes to sustain targeted levels of service with acceptable risk\nResponsibilities: Development of the database website
development of GIS models (desktop and online)
development of data standards for water
wastewater
and stormwater utilities.
Rahul Vemulapallyv
UIM/SWIM Center Conference and PIPEiD Workshop
The Sustainable Water Infrastructure Management (SWIM) Center
UIM
Water Environment Research Foundation (WERF)
Denver Water and Aurora Water are jointly hosting a two-day conference and workshop in Denver
Colorado
Thursday
July 23rd and Friday
July 24th. The event brings together drinking water
wastewater
and storm water professionals to address issues related to pipelines
buried infrastructure and infrastructure management
as well as water quality and water supply.
Development of Performance Prediction Model for Wastewater Pipelines
The purpose of this WERF funded project is to develop a performance index for wastewater pipelines to assess the current performance and a model to predict the performance deterioration on the future to help decision support on asset management for water and wastewater utilities.\nResponsibilities: Doing literature review on related subjects
performing lab tests on the received pipe and soil samples
contacting water and wastewater utilities to receive data
analyzing numerical and image data received from utilities
developing and validating the model in MATLAB.
WATERiD: Water Infrastructure Database
This project is a cooperative effort among Virginia Tech
USEPA
WERF
WATERRF
NSF
and Water Industry to design
populate
manage and maintain a National Web-based Database for Water Infrastructure titled “WATER infrastructure DATABASE (WATERiD)”. Contents in the WATERiD portal include demonstration projects
standards
policy and regulation
lessons learned and best practices
and advanced topics dealing with sustainability and resiliency.
PIPEiD: Pipeline Infrastructure Database
The proposed water infrastructure information system is expected to significantly improve the efficiency of drinking and wastewater infrastructure systems
thereby reducing a significant risk to human health and the environment
if they fail. The simulation capabilities
predictive modeling
and visual communication language developed in this work will have applicability to numerous other applications requiring accurate forecasts and real-time decision making.
Water Infrastructure Database (WATERiD)
The purpose of this federally funded project is to develop a knowledge database for the application of condition assessment and renewal technologies for water and wastewater utilities.\nResponsibilities: Development of the database website
accumulating information on underground locating technologies
creating technology profiles
contacting water and wastewater utilities
and writing case studies regarding locating technology use and data management practices from industry.
Sunil
Virginia Tech