Extending Cyber-Physical Systems to Support Stakeholder Decisions Under Resource and User Constraints: Applications to Intelligent Infrastructure and Social Urban Systems

In recent years, rapid urbanization has imposed greater load demands on physical infrastructure while placing stressors (e.g., pollution, congestion, social inequity) on social systems. Despite these challenges, opportunities are emerging from the unprecedented proliferation of information technologies enabling ubiquitous sensing, cloud computing, and full-scale automation. Together, these advancements enable “intelligent” systems that promise to enhance the operation of the built environment. Even with these advancements, the ability of professionals to “sense for decisions” —data-driven decision processes based on sensed data that have quantifiable returns on investment—remains unrealized for an entire class of problems. In response, this dissertation builds a rigorous foundation enabling stakeholders to use sensor data to inform decisions in two applications: infrastructure asset management and community-engaged decision making. This dissertation aligns sensing strategies with decisions governing infrastructure management by extending the role of reliability methods to quantify system performance. First, the reliability index is used as a scalar measure of the safety (i.e., failure probability) that is extracted from monitoring data to assess structural condition relative to a failure limit state. As an example, long-term data collected from a wireless sensing network (WSN) installed on the Harahan Bridge (Memphis, TN) is used in a reliability framework to track the fatigue life of critical eyebar assemblies. The proposed reliability-based SHM framework is then generalized to formally and more broadly link SHM data with condition ratings (CRs) because inspector-assigned CRs remain the primary starting point for asset management decisions made in practice today. While reliability methods historically quantify safety with respect to a single failure limit state, this work demonstrates that there exist measurable reliability index values associated with “lower” limit states below failure that more richly characterize structural performance and rationally map to CR scales. Consequently, monitoring data can be used to assign CRs based on quantitative information encompassing the measurable damage domain, as opposed to relying on visual inspection. This work reflects the first-ever SHM framework to explicitly map monitoring data to actionable decisions and is validated using a WSN on the Telegraph Road Bridge (TRB) (Monroe, MI). A primary challenge faced by solar-powered WSNs is their stringent energy constraints. For decision-making processes relying on statistical estimation of performance, the utility of data should be considered to optimize the data collection process given these constraints. This dissertation proposes a novel stochastic data collection and transmission policy for WSNs that minimizes the variance of a measured process’ estimated parameters subject to constraints imposed by energy and data buffer sizes, stochastic models of energy and event arrivals, the value of measured data, and temporal death. Numerical results based on one-year of data collected from the TRB illustrate the gains achieved by implementing the optimal policy to obtain response data used to estimate the reliability index. Finally, this dissertation extends the work performed in WSN and sense-for-decision frameworks by exploring their role in community-based decision making. This work poses societal engagement as a necessary entry point to urban sensing efforts because members of under-resourced communities are vulnerable to lack of access to data and information. A novel, low-power WSN architecture is presented that functions as a user-friendly sensing solution that communities can rapidly deploy. Applying this platform, transformative work to “democratize” data is proposed in which members of vulnerable communities collect data and generate insights that inform their decision-making strategies.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162898/1/kaflanig_1.pd

State-of-the-Art Review and Synthesis: A Requirement-based Roadmap for Standardized Predictive Maintenance Automation Using Digital Twin Technologies

Recent digital advances have popularized predictive maintenance (PMx), offering enhanced efficiency, automation, accuracy, cost savings, and independence in maintenance. Yet, it continues to face numerous limitations such as poor explainability, sample inefficiency of data-driven methods, complexity of physics-based methods, and limited generalizability and scalability of knowledge-based methods. This paper proposes leveraging Digital Twins (DTs) to address these challenges and enable automated PMx adoption at larger scales. While we argue that DTs have this transformative potential, they have not yet reached the level of maturity needed to bridge these gaps in a standardized way. Without a standard definition for such evolution, this transformation lacks a solid foundation upon which to base its development. This paper provides a requirement-based roadmap supporting standardized PMx automation using DT technologies. A systematic approach comprising two primary stages is presented. First, we methodically identify the Informational Requirements (IRs) and Functional Requirements (FRs) for PMx, which serve as a foundation from which any unified framework must emerge. Our approach to defining and using IRs and FRs to form the backbone of any PMx DT is supported by the track record of IRs and FRs being successfully used as blueprints in other areas, such as for product development within the software industry. Second, we conduct a thorough literature review spanning fields to determine the ways in which these IRs and FRs are currently being used within DTs, enabling us to point to the specific areas where further research is warranted to support the progress and maturation of requirement-based PMx DTs.Comment: (1)This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Improving Public Transit Accessibility by Leveraging Emerging Multimodal Mobility Options

69A3551747111The rapid growth of new transportation options in the United States has been met with increasing use of these expanded modes of transportation in conjunction with traditional mass transit. However, current engineering models of mass transit systems do not reflect these trends. Existing models tend to (1) only consider traditional public transit (e.g., fix-route buses), and (2) model choices and accessibility for a representative user, with inadequate attention paid to the choices and trade-offs faced by vulnerable populations. The proposed work will advance fundamental knowledge in transportation network modeling by incorporating emerging mobility options, such as shared mobility services, micro-transit, and micro-mobility. This project will develop models, algorithms, and systems used to identify affordable, reliable, and efficient routes that leverage diverse mobility options coupled with conventional mass transit, and ultimately optimize their provisions to low-income populations to improve their accessibility to necessities and essential services

Determination of Deformed Shape from Dynamic Long-Gage Strain Measurement

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Assessment for Reading Instruction, Fourth Edition

Now in a revised and updated fourth edition, this accessible text has given over 100,000 preservice and in-service teachers vital tools for systematic reading assessment in grades K–8. The book explains how to use both formal and informal assessments to evaluate students\u27 strengths and needs in all components of reading. Effective, engaging methods for targeted instruction in each area are outlined. In a convenient large-size format, the book includes 30 reproducible tools, plus an additional multipage assessment in an online-only appendix. Purchasers get access to a companion website where they can download and print the reproducible materials.https://digitalcommons.wcupa.edu/coefaculty_books/1029/thumbnail.jp

Inventory management model based on lean supply chain to increase the service level in a distributor of automotive sector

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.The present research seeks to show the importance of applying process management techniques and food safety norms in the operational processes of the supply chain to know the meaning and the need for an integrated hybrid model. The article reviews the sugarcane distillery sector of Peru and its main operational problems. Based on the literature reviewed and discussed with academics who have knowledge of the food supply chain, an integrated hybrid model was developed to help any distillery with lower levels of competitiveness than its competitors in other sectors, such as pisco, applying techniques of process management and food safety to increase the efficiency of liquor distilleries. The findings confirm that distilleries can increase their efficiency, thanks to the higher performance of their operations after their alignment with the integrated model.Revisión por pare

Enhanced culture method for detection of replication-competent virus in peripheral blood mononuclear cells of HIV type 1-infected individuals

The detection of replication-competent human immunodeficiency virus type 1 (HIV-1) in infected individuals is integral for studies of viral latency and reservoirs of continuing replication during treatment. We describe a modified coculture method to detect/isolate virus from HIV-1-infected individuals with low or undetectable plasma viral loads. We observed a wide range in CD4 and chemokine receptor concentrations on CD4(+) T cells of HIV-1-uninfected donors. We selected cells from donors who expressed high levels of CCR5 after mitogen stimulation to combine in culture with peripheral blood mononuclear cells of HIV-1-infected individuals. Using this donor-enhanced culture method, viruses were isolated from asymptomatic adults with longterm nonprogressive infection, and children receiving effective highly active antiretroviral therapy, whereas parallel cultures with cells expressing lower levels of CCR5 yielded none. Virus was isolated from an individual for whom all previous attempts using reported methods were unsuccessful. Virus growth from cryopreserved cells from this same individual was detected at multiple sampling time points, including a time point at which a sensitive assay to measure 2-LTR (long terminal repeat) circular forms of the viral genome was negative. This will be a useful technique by which to study viral latency and HIV-1 pathogenesis in adult and pediatric populations