Glenn O. Allgood

Wireless industrial sensor networks: framework for QoS assessment and QoS management.

This paper presents a framework that addresses Quality of Service (QoS) for industrial wireless sensor networks as a real-time measurable set of parameters within the context of feedback control, thereby facilitating QoS management. This framework is based on examining the interaction between the industrial control processes and the wireless network. Control theory is used to evaluate the impact of the control/communication interaction, providing a methodology for defining, measuring, and quantifying QoS requirements. An example is presented illustrating the wireless industrial sensor network (WISN) QoS management framework for providing dynamic QoS control within WISN. The example focuses on WISN operating in a time-varying RF interference environment in order to manage application-driven QoS latency constraints.

Model-based high-frequency matched filter arcing diagnostic system based on principal component analysis (PCA) clustering

Arcing in high-energy systems can have a detrimental effect on the operational performance, energy efficiency, life cycle and operating and support costs of a facility. In can occur in motors, switching networks, and transformers and can pose a serious threat to humans who operate or work around the systems. To reduce this risk and increase operational efficiency, it is necessary to develop a capability to diagnose single and multiple arcing events in order to provide an effective measure of system performance. This calculated parameter can then be used to provide an effective measure of system health as it relates to arcing and its deleterious effects. This paper details the development of a model-based matched filter for an antenna that recognizes single and/or multiple arcing events in a direct current motor and calculates a functional measure of activity and a confidence factor based on an estimate of how well the data fit the matched filter model parameters. A principal component analysis is then performed on the descriptive statistics calculated from the models input data stream to develop cluster centers for classifying non- arcing and arching events that are invariant to system operation set point. This approach also has a deployment benefit in that the PCA decreases the computational load on the classifier system by reducing the order of the system.

Aviation security cargo inspection queuing simulation model for material flow and accountability

Beginning in 2010, the U.S. will require that all cargo loaded in passenger aircraft be inspected. This will require more efficient processing of cargo and will have a significant impact on the inspection protocols and business practices of government agencies and the airlines. In this paper, we develop an aviation security cargo inspection queuing simulation model for material flow and accountability that will allow cargo managers to conduct impact studies of current and proposed business practices as they relate to inspection procedures, material flow, and accountability.

Virtual Human: a diagnostic tool for human studies and health effects in the 21st century

The virtual human will be a research/simulation environment having an integrated system of biophysical models, data, and advanced computational algorithms. It will have a Web-based interface for easy, rapid access from several points of entry. The virtual human will serve as a platform for national and international users from governments, academia and industry to investigate the widest range of human biological and physical response to stimuli, be they biological, chemical, or physical. This effort will go far beyond the modeling of anatomy to incorporate refined computational models of whole-body processes, using mechanical and electrical tissue properties, and biology from physiology to biochemical information. The platform will respond mechanistically to varied and potentially iterative stimuli that can be visualized multi- dimensionally. This effort is in the formative stage of a several-year process that will lead to a program that is of similar proportion to the human genome, but will be much more computationally intensive. The main purpose of this paper is to communicate our early ideas about the philosophic basis of the program, to identify some of the applications for which the virtual human would be used, to elicit comments, and to provide a basis to identify prospective collaborators.

Optimizing investments in cyber-security for critical infrastructure

Investments in the cyber-security of critical infrastructure must balance preventing intrusion, detecting a cyber-attack, and mitigating the attackers physical effects on computer controlled equipment. For this purpose, we outline a method for making optimal investment decisions that balance these three aspects of a cyber-defense. The proposed method accounts for the physical process that is being controlled and the relative cost and performance of technologies for prevention, detection, and mitigation. We illustrate the proposed method with a model of a chiller that is based on the supercomputer chillers at Oak Ridge National Laboratory. This model is used to select security capabilities that yields the greatest protection for a fixed budget.

Flow simulation in a 3D model of pig airways and connection to lung sounds

Fundamental to the understanding of the various transport processes within the respiratory system, airway fluid dynamics plays an important role in biomedical research. When air flows through the respiratory tract, it is constantly changing direction through a complex system of curved and bifurcating tubes. As a result, numerical simulations of the airflow through this tracheobronchial system must be capable of resolving such fluid dynamic phenomena as flow separation, recirculation, secondary flows due to centrifugal instabilities, and shear stress variation along the airway surface. Anatomic complexities within the tracheobronchial tree, such as sharp carinal regions at asymmetric bifurcations, have motivated the application of the incompressible Computational Fluid Dynamics code PHI3D to the modeling of airflow. Developed at ORNL, PHI3D implements the new Continuity Constraint Method. Using a finite-element methodology, complex geometries can be easily simulated with PHI3D using unstructured grids. A time- accurate integration scheme allows the simulation of both transient and steady-state flows. A realistic geometry model of the central airways for the fluid flow studies was obtained from pig lungs using a new high resolution x-ray computed tomography system developed at ORNL for generating 3D images of the internal structure of laboratory animals.

An energy signature scheme for steam trap assessment and flow rate estimation using pipe-induced acoustic measurements

The US Congress has passed legislation dictating that all government agencies establish a plan and process for improving energy efficiencies at their sites. In response to this legislation, Oak Ridge National Laboratory (ORNL) has recently conducted a pilot study to explore the deployment of a wireless sensor system for a real-time measurement-based energy efficiency optimization framework within the steam distribution system within the ORNL campus. We make assessments on the real-time status of the distribution system by observing the state measurements of acoustic sensors mounted on the steam pipes/traps/valves. In this paper, we describe a spectral-based energy signature scheme that interprets acoustic vibration sensor data to estimate steam flow rates and assess steam traps health status. Experimental results show that the energy signature scheme has the potential to identify different steam trap health status and it has sufficient sensitivity to estimate steam flow rate. Moreover, results indicate a nearly quadratic relationship over the test region between the overall energy signature factor and flow rate in the pipe. The analysis based on estimated steam flow and steam trap status helps generate alerts that enable operators and maintenance personnel to take remedial action. The goal is to achieve significant energy-saving in steam lines by monitoring and acting on leaking steam pipes/traps/valves.

Capacity utilization study for aviation security cargo inspection queuing system

In this paper, we conduct performance evaluation study for an aviation security cargo inspection queuing system for material flow and accountability. The queuing model employed in our study is based on discrete-event simulation and processes various types of cargo simultaneously. Onsite measurements are collected in an airport facility to validate the queuing model. The overall performance of the aviation security cargo inspection system is computed, analyzed, and optimized for the different system dynamics. Various performance measures are considered such as system capacity, residual capacity, throughput, capacity utilization, subscribed capacity utilization, resources capacity utilization, subscribed resources capacity utilization, and number of cargo pieces (or pallets) in the different queues. These metrics are performance indicators of the systems ability to service current needs and response capacity to additional requests. We studied and analyzed different scenarios by changing various model parameters such as number of pieces per pallet, number of TSA inspectors and ATS personnel, number of forklifts, number of explosives trace detection (ETD) and explosives detection system (EDS) inspection machines, inspection modality distribution, alarm rate, and cargo closeout time. The increased physical understanding resulting from execution of the queuing model utilizing these vetted performance measures should reduce the overall cost and shipping delays associated with new inspection requirements.

Textile laser-optical system for inspecting fabric structure and form

The American textile industry has lost an estimated 400,000 jobs to offshore competitors since 1980. It is predicted they will lose an additional 600,000 jobs by the year 2002. These losses and their resulting economic threat to the U.S. textile industry can be attributed to the low operating costs of their offshore competition. In order to stem these rising losses, the American textile industry entered into an agreement with the U.S. Department of Energy (DOE) in a program called the American Textile Partnership (AMTEXTM). Since the minimum U.S. labor rate is well above that of its offshore competitors, one of the competitive factors the U.S. industry hopes to gain is a higher quality fabric. To facilitate this, a Computer-Aided Fabric Evaluation (CAFE) System has been developed at Oak Ridge National Laboratory (ORNL) and Lockheed Martin Energy Systems, Inc. (LMES). The system is based on a class 3-a laser and a set of cylindrical lenses allowing for 1-D imaging of single yarns thrown in the fill direction. It has been designed to be located close to the point of fabric formation providing data and information on structure, patterns, and material defects of the fabric as it is being formed.

Pulmonary (cardio) diagnostic system for combat casualty care capable of extracting embedded characteristics of obstructive or restrictive flow

Walter Reed Army Institute of Research and Oak Ridge National Laboratory have developed a prototype pulmonary diagnostic system capable of extracting signatures from adventitious lung sounds that characterize obstructive and/or restrictive flow. Examples of disorders that have been detailed include emphysema, asthma, pulmonary fibrosis, and pneumothorax. The system is based on the premise that acoustic signals associated with pulmonary disorders can be characterized by a set of embedded signatures unique to the disease. The concept is being extended to include cardio signals correlated with pulmonary data to provide an accurate and timely diagnoses of pulmonary function and distress in critically injured soldiers that will allow medical personnel to anticipate the need for accurate therapeutic intervention as well as monitor soldiers whose injuries may lead to pulmonary compromise later. The basic operation of the diagnostic system is as follows: (1) create an image from the acoustic signature based on higher order statistics, (2) deconstruct the image based on a predefined map, (3) compare the deconstructed image with stored images of pulmonary symptoms, and (4) classify the disorder based on a clustering of known symptoms and provide a statistical measure of confidence. The system has produced conformity between adults and infants and provided effective measures of physiology in the presence of noise.