James Garrett - US grants

Proposal # 9980759
PI Dr. James H. Garrett
Title: NMR on a Chip: a Micro-NMR Device for in situ Detection of
Chloride in Concrete


The goal of this Engineering Microsystems: "XYZ" on a Chip project is to investigate the hypothesis that a micro nuclear magnetic resonance (NMR) based detector, defined as all aspects of an NMR other than the magnet and power supply, can detect chloride ion in concrete. The coils, oscillator, and essential electronics of an NMR, typically a large expensive device, are being created on a single chip with the CMOS process. The coil turns are one micron thick and one to two millimeters in diameter. The team includes faculty from civil engineering, chemical engineering, electrical engineering, and physics. The project's first stage is modeling and theoretical analysis of a micro NMR. The second stage consists of experiments aimed at demonstrating that the micro NMR can detect protons. This is a useful intermediate objective because the response of protons is 100 times larger than chloride and the signal can be used for calibration of the chloride detection. The third stage is measuring the concentration of free chloride in concrete. The results of this work underpin a sensor technology that could have a substantial impact on the nation's civil infrastructure. For example, an economical chloride sensor based on NMR and dispersed throughout a bridge deck can trigger remediation that prevents loss of the structure due to corrosion of the steel reinforcement. The broader impact of the project is creation of a technology that could find biomedical and other applications.

Proposal: CMS-9987871
PI: James Garrett
Institution: Carnegie Mellon University
Date: April 20, 2001

ABSTRACT CMS-9987871 " A Knowledge Discovery Framework for Civil Infrastructure Contexts" PI: Garrett, James, Carnegie Mellon University; Christos Faloutsos, Carnegie Mellon University; and Sue McNeil, University of Illinois at Chicago.

The primary objective of this research is to specialize the abstract CRISP-DM (Cross-Industry Standard Process for Data Mining) process model being developed within the Knowledge Discovery in Databases (KDD) community, into a framework for use in civil infrastructure problem domains. With the recent accumulation of domain data, civil infrastructrue researchers have turned to data-intensive techniques to aid their understanding of deterioration mechanisms and usage patterns. During roughly the same time period, researchers in the machine learning, database, and statistical communities began to develop a set of new tools and techniques, known as CRISP-DM, to analyze very large databases. This framework will assist civil infrastructure researchers in systematically applying the CRISP-DM process for their data analysis needs. Such a framework will become vital for civil infrastructure researchers as they begin to analyze the enormous amounts of infrastructure data they have collected. The research team will identify the analyze preliminary case studies in civil infrastructure using the CRISP-DM process. Case studies will be chosen based on the uniqueness of their KDD problem characteristics. Special attention will be paid to those case studies that present challenging issues in data quality and data preparation, the most time-consuming and difficult stages of the process as well as the least-studied. The research team will classify civil infrastructure data analysis needs in terms of CRISP-DM process characteristics. All phases of the process will be addressed, but the data understanding (including data quality), data preparation, and modeling phases will be treated in-depth. The research team will then develop a more specific framework for applying the CRISP-DM process to civil infrastructure analysis needs. The research team will also identify and conduct case studies with which to validate the framework. Finally, the development and deployment of a web-based course and a web repository based on this research will be completed during the final year.

Discussions about infrastructure security and survivability require system-wide comparisons and interdisciplinary approaches. Our consideration of survivability focuses on large-scale economic implications of attacks or vulnerabilities on major infrastructure sectors as defined by the Department of Commerce. We explore the critical connections between core service infrastructure sectors (e.g., telecommunications, electricity, and pipelines) using a total supply chain analysis model originally developed to estimate environmental and energy effects of production in the U.S.

We propose to use publicly available data from the Department of Commerce's Bureau of Economic Analysis to show the actual economic dependencies between critical infrastructures and the service economy in general. The input-output tables of the U.S. economy detail the economic purchases that result between all 500 domestic economic sectors. Specifically, these tables show how much output is generated by each of the sectors, and the amounts of product other sectors purchase from each sector. For example, the model can show not only which sectors use electricity but also how much dollar value of electricity is used to produce goods or services in that sector. These data are real and tangible representations of how dependent service sector businesses are to other businesses within the infrastructure sector and the economy in general.

Of course, the sectors of most interest to us when discussing vulnerabilities are sectors involved with critical infrastructure such as the information sector. Analysis of this kind can lead to new approaches to resource allocation for investments to assure infrastructure capabilities. To this end, we will contribute to the national dialogue on pending threats and risks as a result of targeted infrastructure attacks by providing a quantitative assessment tool that shows the potential connection and failure points present in the economy.

Workshop for the Investigation, Documentation, and Dissemination of National Science Foundation (NSF) Research Validation Testbeds at the National Institute of Standards and Technology (NIST)
Technical Abstract
There is a variety of ongoing research related to intelligent infrastructure for building systems that have special needs related to verification of results. These projects require sophisticated testbeds to realistically and comprehensively evaluate the impact of their findings and products. There are many NSF funded projects, for instance, that could benefit from verifying their findings through the use of testbeds. In correspondence to this there are many potential resources at NIST and other building research centers that may make for excellent testbeds. The Principal Investigators are exploring the intellectual synergies between NSF-funded research and opportunities at NIST to verify and validate research findings. To accomplish this, they are organizing a workshop that brings together a diverse group of NSF and NIST researchers and a diverse group of NIST staff to explore opportunities for mutually beneficial collaboration. The workshop is called the National Advanced Building Infrastructure Testbed (NABIT). The Principal Investigators are organizing this workshop in collaboration with Dr. Kent Reed from the Building and Fire Research Lab at NIST. They are inviting a number of appropriate NIST researchers, NSF grantees, as well as potential grantees in affiliated institutions, including Howard University, a supporting partner in this proposal. The intended outcomes of the workshop are a comprehensive inventory of potential participants in NABIT, a methodology for creating testbeds, a small number of targeted testbeds, an online resource for others, and an internship program for Howard students, run concurrently with the workshop. The targeted testbeds serve as the basis of a future comprehensive proposal to be sent to NSF and other funding institutions.
Abstract
Most high end research focuses on the exploration of advanced ideas and the scientific merit of their findings. Rarely are these findings tested and verified against the rich and complex conditions presented by real world applications. One impediment is the lack of time and money. Another one is the lack of readily available testbeds specially compiled databases and equipment that create realistic conditions for verification. The Principal Investigators propose to organize a workshop to explore the ways to create testbeds that would serve to verify research results in the area of building information systems. Research with these systems can impact critical application areas such as energy efficiency in buildings, sound building operation and maintenance practices, and safe and secure use of facilities. The Investigators propose to conduct a workshop to bring together two key institutional resources: researchers that need to verify their results and research institutions that have testbed potential. The workshop will not only develop the methodology, networking, and information basis for creating these testbeds, but will also provide training and entry opportunities for institutions that are interested in entering this research area, such as Howard University. The Investigators expect the workshop to lead to the creation of a National Advanced Building Infrastructure Testbed (NABIT) and further research support in this area.

The main objective of this research is to investigate and develop spatial analysis and deterioration modeling methods in order to improve understanding of pipe breakage and the prediction of water pipe breaks and deterioration as phenomena in space. American water distribution systems are aging and more frequently presenting problems that are mostly visible as water pipe breaks. Water pipes breaks cause water supply interruption, damage to properties, and water quality issues and should be avoided. Also, as water distribution investment needs grow while available resources shrink, attention has been brought to the way water utilities use their resources to maintain and renew their systems. If the time until breakage of a pipe was known with certainty, maintenance could be planned in advance avoiding the problem that results from pipe breakage. Several studies have been done in order to understand how water systems and their components structural condition behave over time. However, understanding how pipe condition varies in space is also important because the factors that cause deterioration of pipes, such as soil characteristics and surface load, vary over space. Yet, few studies have explicitly targeted the spatial aspect of pipe deterioration.

The major long term social benefit of this research is the improvement of water distribution system condition assessment and the eventual optimization of investment allocation. Expected impacts also include the development of competences to teach our civil and environmental engineering students means of spatial analysis both to the infrastructure management and environmental domains. It is believed that this is an area that is emerging as an important part of the analytical competence of engineers. The experience and the insights provided by this research will be shared with graduate students. In addition, a series of workshops and seminars to share the usefulness of this research work and concepts with practitioners and municipalities will be held. Also, it is expected that this work will also assist in broadening the participation of underrepresented groups in research. Special attention will be given to attract students and to hire research assistants from groups that have been traditionally underrepresented in science and engineering to work on this research.

The objective of this research is to provide accurate, rapid, nearly continuous, and cost-effective assessments of a large population of bridges using the data collected from a set of vehicles equipped with sensors able to capture the dynamic interaction between the vehicles and the bridge. This grant provides funding for the development of a new approach for assessing the health of bridges that uses vehicles with on-board sensors to collect condition information about the bridges over which they travel. The dynamic characteristics of the bridge are affected by the damage in the form of cracks, corrosion, and frozen bearings. The first premise of this research is that these changes will be detectable from the dynamic responses collected from a large number of vehicles travelling over the bridge. A second premise is that the type, location and extent of the damage on the bridge will be classified. The new approach will use multiresolution (MR) signal processing and pattern recognition algorithms to detect and classify bridge damage.

If successful, the results of this research will be beneficial to bridge authorities by leading to the development of a new indirect assessment method for monitoring the health of a large number of bridges using the same instrumented vehicles. The method will have a significant economic impact by providing an efficient and more cost effective method to improve the management of the overall structural condition of bridges. The results of this research will also lead to new signal-processing algorithms that will capture signals collected from vehicles. In addition, knowledge gained during the project will be useful for determining the applicability of this approach to different types of structures. The experience and the insights provided by this research project, which will directly involve two PhD graduate students and a number of undergraduate students, will be transferred in courses and demonstrations both at Carnegie Mellon University and the University of Pittsburgh.