EVALUATING INFRASTRUCTURE PERFORMANCE TO ASSIST FACILITY MANAGEMENT TOWARD SUSTAINABLE SYSTEMS

Civil infrastructure provides essential services for the development of both society and economy. It is very important to manage systems efficiently to ensure sound performance. However, there are challenges in information extraction from available data, which also necessitates the establishment of methodologies and frameworks to assist stakeholders in the decision making process. This research proposes methodologies to evaluate systems performance by maximizing the use of available information, in an effort to build and maintain sustainable systems. Under the guidance of problem formulation from a holistic view proposed by Mukherjee and Muga, this research specifically investigates problem solving methods that measure and analyze metrics to support decision making. Failures are inevitable in system management. A methodology is developed to describe arrival pattern of failures in order to assist engineers in failure rescues and budget prioritization especially when funding is limited. It reveals that blockage arrivals are not totally random. Smaller meaningful subsets show good random behavior. Additional overtime failure rate is analyzed by applying existing reliability models and non-parametric approaches. A scheme is further proposed to depict rates over the lifetime of a given facility system. Further analysis of sub-data sets is also performed with the discussion of context reduction. Infrastructure condition is another important indicator of systems performance. The challenges in predicting facility condition are the transition probability estimates and model sensitivity analysis. Methods are proposed to estimate transition probabilities by investigating long term behavior of the model and the relationship between transition rates and probabilities. To integrate heterogeneities, model sensitivity is performed for the application of non-homogeneous Markov chains model. Scenarios are investigated by assuming transition probabilities follow a Weibull regressed function and fall within an interval estimate. For each scenario, multiple cases are simulated using a Monte Carlo simulation. Results show that variations on the outputs are sensitive to the probability regression. While for the interval estimate, outputs have similar variations to the inputs. Life cycle cost analysis and life cycle assessment of a sewer system are performed comparing three different pipe types, which are reinforced concrete pipe (RCP) and non-reinforced concrete pipe (NRCP), and vitrified clay pipe (VCP). Life cycle cost analysis is performed for material extraction, construction and rehabilitation phases. In the rehabilitation phase, Markov chains model is applied in the support of rehabilitation strategy. In the life cycle assessment, the Economic Input-Output Life Cycle Assessment (EIO-LCA) tools are used in estimating environmental emissions for all three phases. Emissions are then compared quantitatively among alternatives to support decision making.

IMPROVING FLOW DISTRIBUTION IN SMALL-SCALE WATER-SUPPLY SYSTEMS THROUGH THE USE OF FLOW-REDUCING DISCS AND METHODS FOR ANALYZING THE EFFECTIVENESS OF SOLAR POWERED PUMPING FOR A DRINKING WATER SUPPLY IN RURAL PANAMA

As continued global funding and coordination are allocated toward the improvement of access to safe sources of drinking water, alternative solutions may be necessary to expand implementation to remote communities. This report evaluates two technologies used in a small water distribution system in a mountainous region of Panama; solar powered pumping and flow-reducing discs. The two parts of the system function independently, but were both chosen for their ability to mitigate unique issues in the community. The design program NeatWork and flow-reducing discs were evaluated because they are tools taught to Peace Corps Volunteers in Panama. Even when ample water is available, mountainous terrains affect the pressure available throughout a water distribution system. Since the static head in the system only varies with the height of water in the tank, frictional losses from pipes and fittings must be exploited to balance out the inequalities caused by the uneven terrain. Reducing the maximum allowable flow to connections through the installation of flow-reducing discs can help to retain enough residual pressure in the main distribution lines to provide reliable service to all connections. NeatWork was calibrated to measured flow rates by changing the orifice coefficient (θ), resulting in a value of 0.68, which is 10-15% higher than typical values for manufactured flow-reducing discs. NeatWork was used to model various system configurations to determine if a single-sized flow-reducing disc could provide equitable flow rates throughout an entire system. There is a strong correlation between the optimum single-sized flow- reducing disc and the average elevation change throughout a water distribution system; the larger the elevation change across the system, the smaller the recommended uniform orifice size. Renewable energy can jump the infrastructure gap and provide basic services at a fraction of the cost and time required to install transmission lines. Methods for the assessment of solar powered pumping systems as a means for rural water supply are presented and assessed. It was determined that manufacturer provided product specifications can be used to appropriately design a solar pumping system, but care must be taken to ensure that sufficient water can be provided to the system despite variations in solar intensity.

Passive wireless sensor systems can recognize activites of daily living

The ability to determine what activity of daily living a person performs is of interest in many application domains. It is possible to determine the physical and cognitive capabilities of the elderly by inferring what activities they perform in their houses. Our primary aim was to establish a proof of concept that a wireless sensor system can monitor and record physical activity and these data can be modeled to predict activities of daily living. The secondary aim was to determine the optimal placement of the sensor boxes for detecting activities in a room. A wireless sensor system was set up in a laboratory kitchen. The ten healthy participants were requested to make tea following a defined sequence of tasks. Data were collected from the eight wireless sensor boxes placed in specific places in the test kitchen and analyzed to detect the sequences of tasks performed by the participants. These sequence of tasks were trained and tested using the Markov Model. Data analysis focused on the reliability of the system and the integrity of the collected data. The sequence of tasks were successfully recognized for all subjects and the averaged data pattern of tasks sequences between the subjects had a high correlation. Analysis of the data collected indicates that sensors placed in different locations are capable of recognizing activities, with the movement detection sensor contributing the most to detection of tasks. The central top of the room with no obstruction of view was considered to be the best location to record data for activity detection. Wireless sensor systems show much promise as easily deployable to monitor and recognize activities of daily living.

Distribution of quality adjusted life expectancy: A systems approach

Statistical methods are developed which assess survival data for two attributes; (1) prolongation of life, (2) quality of life. Health state transition probabilities correspond to prolongation of life and are modeled as a discrete-time semi-Markov process. Imbedded within the sojourn time of a particular health state are the quality of life transitions. They reflect events which differentiate perceptions of pain and suffering over a fixed time period. Quality of life transition probabilities are derived from the assumptions of a simple Markov process. These probabilities depend on the health state currently occupied and the next health state to which a transition is made. Utilizing the two forms of attributes the model has the capability to estimate the distribution of expected quality adjusted life years (in addition to the distribution of expected survival times). The expected quality of life can also be estimated within the health state sojourn time making more flexible the assessment of utility preferences. The methods are demonstrated on a subset of follow-up data from the Beta Blocker Heart Attack Trial (BHAT). This model contains the structure necessary to make inferences when assessing a general survival problem with a two dimensional outcome. ^

Sm-Nd, Rb-Sr, and He isotopic composition and hydrocarbon gases in rocks and minerals from the Markov Deep, Mid-Atlantic Ridge rift valley

The paper presents characteristics of the Nd and Sr isotopic systems of ultrabasic rocks, gabbroids, plagiogranites, and their minerals as well as data on helium and hydrocarbons in fluid inclusions of the same samples. Materials presented in this publication were obtained by studying samples dredged from the MAR crest zone at 5°-6°N (U/Pb zircon dating, geochemical and petrological-mineralogical studies). It was demonstrated that variations in the isotopic composition of He entrapped in rocks and minerals were controlled by variable degrees of mixing of juvenile He, which is typical of basaltic glass for MAR (DM source), and atmospheric He. Increase in the atmospheric He fraction in plutonic rocks and, to a lesser degree, in their minerals reflects involvement of seawater or hydrated material of the oceanic crust in magmatic and postmagmatic processes. This conclusion finds further support in positive correlation between the fraction of mantle He (R ratio) and 87Sr/86Sr ratio. High-temperature hydration of ultrabasic rocks (amphibolization) was associated with increase in the fraction of mantle He, while their low-temperature hydration (serpentinization) was accompanied by drastic decrease in this fraction and significant increase in 87Sr/86Sr ratio. Insignificant variations in 143Nd/144Nd (close to 0.5130) and 87Sr/86Sr (0.7035) in most of gabbroids and plagiogranites as well as the fraction of mantle He in these rocks, amphibolites, and their ore minerals indicate that the melts were derived from the depleted mantle. Similar e-Nd values of gabbroids, plagiogranites, and fresh harzburgites (6.77-8.39) suggest that these rocks were genetically related to a single mantle source. e-Nd value of serpentinized lherzolites (2.62) likely reflects relations of these relatively weakly depleted mantle residues to another source. Aforementioned characteristics of the rocks generally reflect various degrees of mixing of depleted mantle components with crustal components (seawater) during metamorphic and hydrothermal processes that accompanied formation of the oceanic crust.

On-road visual vehicle tracking using Markov chain Monte Carlo with metropolis sampling

In this study, a method for vehicle tracking through video analysis based on Markov chain Monte Carlo (MCMC) particle filtering with metropolis sampling is proposed. The method handles multiple targets with low computational requirements and is, therefore, ideally suited for advanced-driver assistance systems that involve real-time operation. The method exploits the removed perspective domain given by inverse perspective mapping (IPM) to define a fast and efficient likelihood model. Additionally, the method encompasses an interaction model using Markov Random Fields (MRF) that allows treatment of dependencies between the motions of targets. The proposed method is tested in highway sequences and compared to state-of-the-art methods for vehicle tracking, i.e., independent target tracking with Kalman filtering (KF) and joint tracking with particle filtering. The results showed fewer tracking failures using the proposed method.

A generalized Markov sampler

A recent development of the Markov chain Monte Carlo (MCMC) technique is the emergence of MCMC samplers that allow transitions between different models. Such samplers make possible a range of computational tasks involving models, including model selection, model evaluation, model averaging and hypothesis testing. An example of this type of sampler is the reversible jump MCMC sampler, which is a generalization of the Metropolis-Hastings algorithm. Here, we present a new MCMC sampler of this type. The new sampler is a generalization of the Gibbs sampler, but somewhat surprisingly, it also turns out to encompass as particular cases all of the well-known MCMC samplers, including those of Metropolis, Barker, and Hastings. Moreover, the new sampler generalizes the reversible jump MCMC. It therefore appears to be a very general framework for MCMC sampling. This paper describes the new sampler and illustrates its use in three applications in Computational Biology, specifically determination of consensus sequences, phylogenetic inference and delineation of isochores via multiple change-point analysis.

Uniqueness criteria for continuous-time Markov chains with general transition structures

We derive necessary and sufficient conditions for the existence of bounded or summable solutions to systems of linear equations associated with Markov chains. This substantially extends a famous result of G. E. H. Reuter, which provides a convenient means of checking various uniqueness criteria for birth-death processes. Our result allows chains with much more general transition structures to be accommodated. One application is to give a new proof of an important result of M. F. Chen concerning upwardly skip-free processes. We then use our generalization of Reuter's lemma to prove new results for downwardly skip-free chains, such as the Markov branching process and several of its many generalizations. This permits us to establish uniqueness criteria for several models, including the general birth, death, and catastrophe process, extended branching processes, and asymptotic birth-death processes, the latter being neither upwardly skip-free nor downwardly skip-free.

Pitch jump probability measures for the analysis of snoring sounds in apnea

Obstructive sleep apnea (OSA) is a highly prevalent disease in which upper airways are collapsed during sleep, leading to serious consequences. The gold standard of diagnosis, called polysomnography (PSG), requires a full-night hospital stay connected to over ten channels of measurements requiring physical contact with sensors. PSG is inconvenient, expensive and unsuited for community screening. Snoring is the earliest symptom of OSA, but its potential in clinical diagnosis is not fully recognized yet. Diagnostic systems intent on using snore-related sounds (SRS) face the tough problem of how to define a snore. In this paper, we present a working definition of a snore, and propose algorithms to segment SRS into classes of pure breathing, silence and voiced/unvoiced snores. We propose a novel feature termed the 'intra-snore-pitch-jump' (ISPJ) to diagnose OSA. Working on clinical data, we show that ISPJ delivers OSA detection sensitivities of 86-100% while holding specificity at 50-80%. These numbers indicate that snore sounds and the ISPJ have the potential to be good candidates for a take-home device for OSA screening. Snore sounds have the significant advantage in that they can be conveniently acquired with low-cost non-contact equipment. The segmentation results presented in this paper have been derived using data from eight patients as the training set and another eight patients as the testing set. ISPJ-based OSA detection results have been derived using training data from 16 subjects and testing data from 29 subjects.

Entropy generation for microscale forced convection: effects of different thermal boundary conditions, velocity slip, temperature jump, viscous dissipation, and duct geometry

This work presents closed form solutions for fully developed temperature distribution and entropy generation due to forced convection in microelectromechanical systems (MEMS) in the Slip-flow regime, for which the Knudsen number lies within the range 0.001