Sistemas de gestión de puentes : optimización de estrategias de mantenimiento : implementación en redes locales de carreteras

En la actualidad, y en consonancia con la tendencia de “sostenibilidad” extendida a todos los campos y parcelas de la ciencia, nos encontramos con un área de estudio basado en la problemática del inevitable deterioro de las estructuras existentes, y la gestión de las acciones a realizar para mantener las condiciones de servicio de los puentes y prolongar su vida útil. Tal y como se comienza a ver en las inversiones en los países avanzados, con una larga tradición en el desarrollo de sus infraestructuras, se muestra claramente el nuevo marco al que nos dirigimos. Las nuevas tendencias van encaminadas cada vez más a la conservación y mantenimiento, reduciéndose las partidas presupuestarias destinadas a nuevas actuaciones, debido a la completa vertebración territorial que se ha ido instaurando en estos países, entre los que España se encuentra. Este nutrido patrimonio de infraestructuras viarias, que cuentan a su vez con un importante número de estructuras, hacen necesarias las labores de gestión y mantenimiento de los puentes integrantes en las mismas. Bajo estas premisas, la tesis aborda el estado de desarrollo de la implementación de los sistemas de gestión de puentes, las tendencias actuales e identificación de campos por desarrollar, así como la aplicación específica a redes de carreteras de escasos recursos, más allá de la Red Estatal. Además de analizar las diversas metodologías de formación de inventarios, realización de inspecciones y evaluación del estado de puentes, se ha enfocado, como principal objetivo, el desarrollo de un sistema específico de predicción del deterioro y ayuda a la toma de decisiones. Este sistema, adicionalmente a la configuración tradicional de criterios de formación de bases de datos de estructuras e inspecciones, plantea, de forma justificada, la clasificación relativa al conjunto de la red gestionada, según su estado de condición. Eso permite, mediante técnicas de optimización, la correcta toma de decisiones a los técnicos encargados de la gestión de la red. Dentro de los diversos métodos de evaluación de la predicción de evolución del deterioro de cada puente, se plantea la utilización de un método bilineal simplificado envolvente del ajuste empírico realizado y de los modelos markovianos como la solución más efectiva para abordar el análisis de la predicción de la propagación del daño. Todo ello explotando la campaña experimenta realizada que, a partir de una serie de “fotografías técnicas” del estado de la red de puentes gestionados obtenidas mediante las inspecciones realizadas, es capaz de mejorar el proceso habitual de toma de decisiones. Toda la base teórica reflejada en el documento, se ve complementada mediante la implementación de un Sistema de Gestión de Puentes (SGP) específico, adaptado según las necesidades y limitaciones de la administración a la que se ha aplicado, en concreto, la Dirección General de Carreteras de la Junta de Comunidades de Castilla-La Mancha, para una muestra representativa del conjunto de puentes de la red de la provincia de Albacete, partiendo de una situación en la que no existe, actualmente, un sistema formal de gestión de puentes. Tras un meditado análisis del estado del arte dentro de los Capítulos 2 y 3, se plantea un modelo de predicción del deterioro dentro del Capítulo 4 “Modelo de Predicción del Deterioro”. De la misma manera, para la resolución del problema de optimización, se justifica la utilización de un novedoso sistema de optimización secuencial elegido dentro del Capítulo 5, los “Algoritmos Evolutivos”, en sus diferentes variantes, como la herramienta matemática más correcta para distribuir adecuadamente los recursos económicos dedicados a mantenimiento y conservación de los que esta administración pueda disponer en sus partidas de presupuesto a medio plazo. En el Capítulo 6, y en diversos Anexos al presente documento, se muestran los datos y resultados obtenidos de la aplicación específica desarrollada para la red local analizada, utilizando el modelo de deterioro y optimización secuencial, que garantiza la correcta asignación de los escasos recursos de los que disponen las redes autonómicas en España. Se plantea con especial interés la implantación de estos sistemas en la red secundaria española, debido a que reciben en los últimos tiempos una mayor responsabilidad de gestión, con recursos cada vez más limitados. Finalmente, en el Capítulo 7, se plantean una serie de conclusiones que nos hacen reflexionar de la necesidad de comenzar a pasar, en materia de gestión de infraestructuras, de los estudios teóricos y los congresos, hacia la aplicación y la práctica, con un planteamiento que nos debe llevar a cambios importantes en la forma de concebir la labor del ingeniero y las enseñanzas que se imparten en las escuelas. También se enumeran las aportaciones originales que plantea el documento frente al actual estado del arte. Se plantean, de la misma manera, las líneas de investigación en materia de Sistemas de Gestión de Puentes que pueden ayudar a refinar y mejorar los actuales sistemas utilizados. In line with the development of "sustainability" extended to all fields of science, we are faced with the inevitable and ongoing deterioration of existing structures, leading nowadays to the necessary management of maintaining the service conditions and life time extension of bridges. As per the increased amounts of money that can be observed being spent in the countries with an extensive and strong tradition in the development of their infrastructure, the trend can be clearly recognized. The new tendencies turn more and more towards conservation and maintenance, reducing programmed expenses for new construction activities, in line with the already wellestablished territorial structures, as is the case for Spain. This significant heritage of established road infrastructure, consequently containing a vast number of structures, imminently lead to necessary management and maintenance of the including bridges. Under these conditions, this thesis focusses on the status of the development of the management implementation for bridges, current trends, and identifying areas for further development. This also includes the specific application to road networks with limited resources, beyond the national highways. In addition to analyzing the various training methodologies, inventory inspections and condition assessments of bridges, the main objective has been the development of a specific methodology. This methodology, in addition to the traditional system of structure and inspection database training criteria, sustains the classification for the entire road network, according to their condition. This allows, through optimization techniques, for the correct decision making by the technical managers of the network. Among the various methods for assessing the evolution forecast of deterioration of each bridge, a simplified bilinear envelope adjustment made empirical method and Markov models as the most effective solution to address the analysis of predicting the spread of damage, arising from a "technical snapshot" obtained through inspections of the condition of the bridges included in the investigated network. All theoretical basis reflected in the document, is completed by implementing a specific Bridges Management System (BMS), adapted according to the needs and limitations of the authorities for which it has been applied, being in this case particularly the General Highways Directorate of the autonomous region of Castilla-La Mancha, for a representative sample of all bridges in the network in the province of Albacete, starting from a situation where there is currently no formal bridge management system. After an analysis of the state of the art in Chapters 2 and 3, a new deterioration prediction model is developed in Chapter 4, "Deterioration Prediction Model". In the same way, to solve the optimization problem is proposed the use of a singular system of sequential optimization elected under Chapter 5, the "Evolutionary Algorithms", the most suitable mathematical tool to adequately distribute the economic resources for maintenance and conservation for mid-term budget planning. In Chapter 6, and in the various appendices, data and results are presented of the developed application for the analyzed local network, from the optimization model, which guarantees the correct allocation of scarce resources at the disposal of authorities responsible for the regional networks in Spain. The implementation of these systems is witnessed with particular interest for the Spanish secondary network, because of the increasing management responsibility, with decreasing resources. Chapter 7 presents a series of conclusions that triggers to reconsider shifting from theoretical studies and conferences towards a practical implementation, considering how to properly conceive the engineering input and the related education. The original contributions of the document are also listed. In the same way, the research on the Bridges Management System can help evaluating and improving the used systematics.

MINLP Optimization Algorithm for the Synthesis of Heat and Work Exchange Networks

This paper introduces a new optimization model for the simultaneous synthesis of heat and work exchange networks. The work integration is performed in the work exchange network (WEN), while the heat integration is carried out in the heat exchanger network (HEN). In the WEN synthesis, streams at high-pressure (HP) and low-pressure (LP) are subjected to pressure manipulation stages, via turbines and compressors running on common shafts and stand-alone equipment. The model allows the use of several units of single-shaft-turbine-compressor (SSTC), as well as helper motors and generators to respond to any shortage and/or excess of energy, respectively, in the SSTC axes. The heat integration of the streams occurs in the HEN between each WEN stage. Thus, as the inlet and outlet streams temperatures in the HEN are dependent of the WEN design, they must be considered as optimization variables. The proposed multi-stage superstructure is formulated in mixed-integer nonlinear programming (MINLP), in order to minimize the total annualized cost composed by capital and operational expenses. A case study is conducted to verify the accuracy of the proposed approach. The results indicate that the heat integration between the WEN stages is essential to enhance the work integration, and to reduce the total cost of process due the need of a smaller amount of hot and cold utilities.

Large scale optimization of a sour water stripping plant using surrogate models

In this work, we propose a new methodology for the large scale optimization and process integration of complex chemical processes that have been simulated using modular chemical process simulators. Units with significant numerical noise or large CPU times are substituted by surrogate models based on Kriging interpolation. Using a degree of freedom analysis, some of those units can be aggregated into a single unit to reduce the complexity of the resulting model. As a result, we solve a hybrid simulation-optimization model formed by units in the original flowsheet, Kriging models, and explicit equations. We present a case study of the optimization of a sour water stripping plant in which we simultaneously consider economics, heat integration and environmental impact using the ReCiPe indicator, which incorporates the recent advances made in Life Cycle Assessment (LCA). The optimization strategy guarantees the convergence to a local optimum inside the tolerance of the numerical noise.

Integrating spatial optimization and cellular automata for evaluating urban change

Urban growth and change presents numerous challenges for planners and policy makers. Effective and appropriate strategies for managing growth and change must address issues of social, environmental and economic sustainability. Doing so in practical terms is a difficult task given the uncertainty associated with likely growth trends not to mention the uncertainty associated with how social and environmental structures will respond to such change. An optimization based approach is developed for evaluating growth and change based upon spatial restrictions and impact thresholds. The spatial optimization model is integrated with a cellular automata growth simulation process. Application results are presented and discussed with respect to possible growth scenarios in south east Queensland, Australia.

Design and implementation of a windows-based parallel computing environment for large scale optimization

A parallel computing environment to support optimization of large-scale engineering systems is designed and implemented on Windows-based personal computer networks, using the master-worker model and the Parallel Virtual Machine (PVM). It is involved in decomposition of a large engineering system into a number of smaller subsystems optimized in parallel on worker nodes and coordination of subsystem optimization results on the master node. The environment consists of six functional modules, i.e. the master control, the optimization model generator, the optimizer, the data manager, the monitor, and the post processor. Object-oriented design of these modules is presented. The environment supports steps from the generation of optimization models to the solution and the visualization on networks of computers. User-friendly graphical interfaces make it easy to define the problem, and monitor and steer the optimization process. It has been verified by an example of a large space truss optimization. (C) 2004 Elsevier Ltd. All rights reserved.

Who will see me? The impact of type of audience on willingness to display group-mediated attitude-intention consistency

The present study examined the role that group norms, group identification, and imagined audience (in-group vs. out-group) play in attitude-behavior processes. University students (N = 187) participated in a study concerned with the prediction of consumer behavior. Attitudes toward drinking their preferred beer, subjective norm, perceived behavioral control, group norm, and group identification were assessed. Intentions and perceived audience reactions to consumption were assessed. As expected, group norms, identification, and imagined audience interacted to influence likelihood of drinking one's preferred beer and perceived audience reactions. High identifiers were more responsive to group norms in the presence of an in-group audience than an out-group audience. The present results indicate that audience concerns impact upon the relationship between attitude., and behavior.

Improving the economic decision making capability and viability of Chinese wool textile mills

The successful restructuring of Chinese industries is of immense importance not only for the continued development of China but also to the stability of the world economy. The transformation of the Chinese wool textile industry illustrates well the many problems and pressures currently facing most Chinese industries. The Chinese wool textile industry has undergone major upheaval and restructuring in its drive to modernize and take advantage of developments in world textile markets. Macro level ownership and administrative reforms are well advanced as is the uptake of new technology and equipment. However, the changing market and institutional environment also demands an increasing level of sophistication in mill management decisions including product selection, input procurement, product pricing, investment appraisal, cost analysis and proactive identification of new market and growth opportunities. This paper outlines a series of analyses that have been integrated into a decision-making model designed to assist mill managers with these decisions. Features of the model include a whole-of-mill approach, a design based on existing mill structures and information systems, and the capacity for the model to be tailored to individual mills. All of these features facilitate the adoption of the model by time and resource constrained managers seeking to maintain the viability of their enterprises in the face of extremely dynamic market conditions.

Optimum Trajectory of Dynamic Input-Output Balance Model for Open Economy

When export and import is connected with output of basic production, and criterion functional represents a final state of economy, the generalization of classical qualitative results of the main-line theory on a case of dynamic input-output balance optimization model for open economy is given.

Mathematical Optimization for the Train Timetabling Problem

AMS Subj. Classification: 90C57; 90C10;

Decision support system for production control: Multiple criteria decision making in practice

This paper presents a development of decision support systems for solving scheduling problems. It consists of two parts — the first describing the production processes which can be handled by the system and the second describing how the system works.

An automatic tuning strategy for local fuzzy logic ramp metering algorithm using Particle Swarm Optimization (PSO)

Freeway systems are becoming more congested each day. One contribution to freeway traffic congestion comprises platoons of on-ramp traffic merging into freeway mainlines. As a relatively low-cost countermeasure to the problem, ramp meters are being deployed in both directions of an 11-mile section of I-95 in Miami-Dade County, Florida. The local Fuzzy Logic (FL) ramp metering algorithm implemented in Seattle, Washington, has been selected for deployment. The FL ramp metering algorithm is powered by the Fuzzy Logic Controller (FLC). The FLC depends on a series of parameters that can significantly alter the behavior of the controller, thus affecting the performance of ramp meters. However, the most suitable values for these parameters are often difficult to determine, as they vary with current traffic conditions. Thus, for optimum performance, the parameter values must be fine-tuned. This research presents a new method of fine tuning the FLC parameters using Particle Swarm Optimization (PSO). PSO attempts to optimize several important parameters of the FLC. The objective function of the optimization model incorporates the METANET macroscopic traffic flow model to minimize delay time, subject to the constraints of reasonable ranges of ramp metering rates and FLC parameters. To further improve the performance, a short-term traffic forecasting module using a discrete Kalman filter was incorporated to predict the downstream freeway mainline occupancy. This helps to detect the presence of downstream bottlenecks. The CORSIM microscopic simulation model was selected as the platform to evaluate the performance of the proposed PSO tuning strategy. The ramp-metering algorithm incorporating the tuning strategy was implemented using CORSIM's run-time extension (RTE) and was tested on the aforementioned I-95 corridor. The performance of the FLC with PSO tuning was compared with the performance of the existing FLC without PSO tuning. The results show that the FLC with PSO tuning outperforms the existing FL metering, fixed-time metering, and existing conditions without metering in terms of total travel time savings, average speed, and system-wide throughput.

Essays in Empirical Operations Management: Bayesian Learning of Service Quality and Structural Estimation of Complementary Product Pricing and Inventory Management

This dissertation contributes to the rapidly growing empirical research area in the field of operations management. It contains two essays, tackling two different sets of operations management questions which are motivated by and built on field data sets from two very different industries --- air cargo logistics and retailing.

The first essay, based on the data set obtained from a world leading third-party logistics company, develops a novel and general Bayesian hierarchical learning framework for estimating customers' spillover learning, that is, customers' learning about the quality of a service (or product) from their previous experiences with similar yet not identical services. We then apply our model to the data set to study how customers' experiences from shipping on a particular route affect their future decisions about shipping not only on that route, but also on other routes serviced by the same logistics company. We find that customers indeed borrow experiences from similar but different services to update their quality beliefs that determine future purchase decisions. Also, service quality beliefs have a significant impact on their future purchasing decisions. Moreover, customers are risk averse; they are averse to not only experience variability but also belief uncertainty (i.e., customer's uncertainty about their beliefs). Finally, belief uncertainty affects customers' utilities more compared to experience variability.

The second essay is based on a data set obtained from a large Chinese supermarket chain, which contains sales as well as both wholesale and retail prices of un-packaged perishable vegetables. Recognizing the special characteristics of this particularly product category, we develop a structural estimation model in a discrete-continuous choice model framework. Building on this framework, we then study an optimization model for joint pricing and inventory management strategies of multiple products, which aims at improving the company's profit from direct sales and at the same time reducing food waste and thus improving social welfare.

Collectively, the studies in this dissertation provide useful modeling ideas, decision tools, insights, and guidance for firms to utilize vast sales and operations data to devise more effective business strategies.

Delay Assignment Optimization Strategies at Pre- Tactical and Tactical Levels

This paper compares different optimization strategies for the minimization of flight and passenger delays at two levels: pre-tactical, with on-ground delay at origin, and tactical, with airborne delay close to the destination airport. The optimization model is based on the ground holding problem and uses various cost functions. The scenario considered takes place in a busy European airport and includes realistic values of traffic. Uncertainty is introduced in the model for the passenger allocation, minimum time required for turnaround and tactical uncertainty. Performance of the various optimization processes is presented and compared to ratio by schedule results.

Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts

We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.

The Use of Multi-Criteria Decision Analysis in Performing Alternatives Assessment and Comparative Risk Analysis: The Case Study of Codling Moth Pesticides

Thesis (Ph.D.)--University of Washington, 2016-08