Use of Fiber Reinforced Polymer Composite Cable for Post-tensioning Application

Corrosion of steel tendons is a major problem for post-tensioned concrete, especially because corrosion of the steel strands is often hard to detect inside grouted ducts. Non-metallic tendons can serve as an alternative material to steel for post-tensioning applications. Carbon fiber reinforced polymer (CFRP), given its higher strength and elastic modulus, as well as excellent durability and fatigue strength, is the most practical option for post-tensioning applications. The primary objective of this research project was to assess the feasibility of the use of innovative carbon fiber reinforced polymer (CFRP) tendons and to develop guidelines for CFRP in post-tensioned bridge applications, including segmental bridges and pier caps. An experimental investigation and a numerical simulation were conducted to compare the performance of a scaled segmental bridge model, post-tensioned with two types of carbon fiber strands and steel strands. The model was tested at different prestress levels and at different loading configurations. While the study confirms feasibility of both types of carbon fiber strands for segmental bridge applications, and their similar serviceability behavior, strands with higher elastic modulus could improve structural performance and minimize displacements beyond service loads. As the second component of the project, a side-by-side comparison of two types of carbon fiber strands against steel strands was conducted in a scaled pier cap model. Two different strand arrangements were used for post-tensioning, with eight and six strands, respectively representing an over-design and a slight under-design relative to the factored demand. The model was tested under service and factored loads. The investigation confirmed the feasibility of using carbon fiber strands in unbonded post-tensioning of pier caps. Considering both serviceability and overload conditions, the general performance of the pier cap model was deemed acceptable using either type of carbon fiber strands and quite comparable to that of steel strands. In another component of this research, creep stress tests were conducted with carbon fiber composite cable (CFCC). The anchorages for all the specimens were prepared using a commercially available expansive grout. Specimens withstood 95% of the guaranteed capacity provided by the manufacturer for a period of five months, without any sign of rupture.

Demanda y control de la tarea y presencia de síntomas de estrés y osteo-musculares en personal de una institución hospitalaria de IV nivel, Bogotá, 2016.

El ejercicio de labores asistenciales en el personal de la salud, las largas horas de trabajo y la responsabilidad en la ejecución de sus tareas, llevan consigo la exposición a riesgos psicosociales; que de no ser debidamente controlados pueden llevar al individuo a generar respuestas inadecuadas a nivel cognitivo, emocional e intelectual, las cuales se manifiestan en algunos casos con la aparición de sintomatología osteomuscular y/o asociada al estrés. OBJETIVO Identificar la relación entre las demandas de la tarea, el control sobre las mismas y la presencia e intensidad de síntomas de estrés y osteo-musculares en médicos, especialistas y personal de enfermería de una institución hospitalaria de IV nivel en Bogotá. Métodos Estudio de corte transversal en una muestra de 100 profesionales de la salud. Se utilizaron tres instrumentos: cuestionario Nórdico para la detección y análisis de síntomas músculo esqueléticos, cuestionario Karasek para identificar la percepción del trabajo y la relación del entorno profesional y el cuestionario de Estrés del Ministerio de la Protección Social validado para la población colombiana. Se obtuvo previa autorización del Comité de Investigaciones y Comité de Ética del Hospital. El análisis estadístico se realizó con el IBM SPSS Statistics versión 2.0 Resultados Se observó que los síntomas osteomusculares con mayor prevalencia estuvieron relacionados con afectaciones en espalda 43% y cuello 36%; no se observan diferencias estadísticamente significativas entre los distintos profesionales. En cuanto a presencia de sintomatología asociada al estrés, la mayor prevalencia se presentó en síntomas osteomusculares en cuello y espalda en el 84% de los casos, dolor de cabeza en el 74%, trastornos del sueño y cansancio en el 64% y percepción de sobrecarga laboral en el 63%. Para el análisis de prevalencia de los factores psicosociales laborales se utilizó la clasificación de la combinación de altas o bajas demandas y alto o bajo control, el resultado de estos teniendo en cuenta el modelo Demanda-control fue la siguiente: trabajo de alta tensión 34%; trabajo activo 40%; trabajo aburrido 13% y trabajo pasivo 13%. Se encontró una asociación entre la sintomatología y las variables toma de decisiones en médicos especialistas (OR 3,12; IC 95%: 2,80 – 3,49) lo que ratifica que este tipo de profesional tiene una mayor libertad para generar decisiones en su actuar médico y control sobre la tarea para especialistas (OR 3,23; IC 95%: 2,82 – 3,70) y enfermeros jefes (OR 3,36; IC 95%: 2,91 – 3,89); lo que permite inferir que cada uno de estos profesionales posee las herramientas para asumir las exigencias y dar respuesta a los distintos aspectos que están ligados a la tarea. Conclusiones: La presencia de síntomas osteo musculares en zonas como cuello y espalda son propios de la actividad del personal de la salud y se asocia a las posturas inadecuadas y el puesto de trabajo, así como al estrés. En cuanto a la sintomatología asociada al estrés se ratifica la presencia de sintomatología osteo muscular (cuello y espalda), como manifestaciones asociadas al cansancio, trastornos del sueño, sobrecarga laboral, dolor de cabeza y en menor porcentaje dificultades para relacionarse con otros. Respecto a los factores de riesgo psicosocial, se observó que el trabajo activo es la condición predominante en el personal de la salud, pero se observa además que un porcentaje importante experimenta episodios de tensión laboral, asociados a condiciones propias de las demandas psicológicas y el control sobre la tarea. Por lo anterior, se deben establecer acciones encaminadas a favorecer espacios saludables, y programas tendientes a la mejora de las condiciones de tal manera que disminuya la presencia de sintomatología osteomuscular y/o sintomatología derivada del estrés.

Asociaciones público privadas para la infraestructura social en salud: hacia la identificación de pautas para la definición de un modelo colombiano

Las asociaciones público privadas "APP" han sido utilizadas para distribuir riesgos y fomentar el desarrollo de los países a través de la provisión de infraestructura. Así, se implementan para proveer bienes y servicios públicos tanto en los sectores de infraestructura productiva (carreteras, puertos, aeropuertos, trenes), como en el sector de infraestructura social (escuelas, universidades, hospitales, edificaciones públicas, etc.). En Colombia, ante la escasez de recursos públicos y la necesidad de formular posiibles soluciones a la crisis del sector salud, surge como una posible solución el modelo de APP consagrado en la Ley 1508 de 2008.

Structural steel design with BIM technology - interventions on a three buildings block in Deruta (PG)

The aim of this thesis is to use the developments, advantages and applications of "Building Information Modelling" (BIM) with emphasis on the discipline of structural design for steel building located in Perugia. BIM was mainly considered as a new way of planning, constructing and operating buildings or infrastructures. It has been found to offer greater opportunities for increased efficiency, optimization of resources and generally better management throughout the life cycle of a facility. BIM increases the digitalization of processes and offers integrated and collaborative technologies for design, construction and operation. To understand BIM and its benefits, one must consider all phases of a project. Higher initial design costs often lead to lower construction and operation costs. Creating data-rich digital models helps to better predict and coordinate the construction phases and operation of a building. One of the main limitations identified in the implementation of BIM is the lack of knowledge and qualified professionals. Certain disciplines such as structural and mechanical design depend on whether the main contractor, owner, general contractor or architect need to use or apply BIM to their projects. The existence of a supporting or mandatory BIM guideline may then eventually lead to its adoption. To test the potential of the BIM adoption in the steel design process, some models were developed taking advantage of a largely diffuse authoring software (Autodesk Revit), to produce construction drawings and also material schedule that were needed in order to estimate quantities and features of a real steel building. Once the model has been built the whole process has been analyzed and then compared with the traditional design process of steel structure. Many relevant aspect in term of clearness and also in time spent were shown and lead to final conclusions about the benefits from BIM methodology.

A finite-population revenue management model and a risk-ratio procedure for the joint estimation of population size and parameters

Many dynamic revenue management models divide the sale period into a finite number of periods T and assume, invoking a fine-enough grid of time, that each period sees at most one booking request. These Poisson-type assumptions restrict the variability of the demand in the model, but researchers and practitioners were willing to overlook this for the benefit of tractability of the models. In this paper, we criticize this model from another angle. Estimating the discrete finite-period model poses problems of indeterminacy and non-robustness: Arbitrarily fixing T leads to arbitrary control values and on the other hand estimating T from data adds an additional layer of indeterminacy. To counter this, we first propose an alternate finite-population model that avoids this problem of fixing T and allows a wider range of demand distributions, while retaining the useful marginal-value properties of the finite-period model. The finite-population model still requires jointly estimating market size and the parameters of the customer purchase model without observing no-purchases. Estimation of market-size when no-purchases are unobservable has rarely been attempted in the marketing or revenue management literature. Indeed, we point out that it is akin to the classical statistical problem of estimating the parameters of a binomial distribution with unknown population size and success probability, and hence likely to be challenging. However, when the purchase probabilities are given by a functional form such as a multinomial-logit model, we propose an estimation heuristic that exploits the specification of the functional form, the variety of the offer sets in a typical RM setting, and qualitative knowledge of arrival rates. Finally we perform simulations to show that the estimator is very promising in obtaining unbiased estimates of population size and the model parameters.

Building synergies in development research: The application of the mosaic model to animal health research

Development research has responded to a number of charges over the past few decades. For example, when traditional research was accused of being 'top-down', the response was participatory research, linking the 'receptors' to the generators of research. As participatory processes were recognised as producing limited outcomes, the demand-led agenda was born. In response to the alleged failure of research to deliver its products, the 'joined-up' model, which links research with the private sector, has become popular. However, using examples from animal-health research, this article demonstrates that all the aforementioned approaches are seriously limited in their attempts to generate outputs to address the multi-faceted problems facing the poor. The article outlines a new approach to research: the Mosaic Model. By combining different knowledge forms, and focusing on existing gaps, the model aims to bridge basic and applied findings to enhance the efficiency and value of research, past, present, and future.

Greenhouse gas emission scenario modeling for cities using the PURGE model

Cities globally are in the midst of taking action to reduce greenhouse gas (GHG) emissions. After the vital step of emissions quantification, strategies must be developed to detail how emissions reductions targets will be achieved. The Pathways to Urban Reductions in Greenhouse Gas Emissions (PURGE) model allows the estimation of emissions from four pertinent urban sectors: electricity generation, buildings, private transportation, and waste. Additionally, the carbon storage from urban and regional forests is modeled. An emissions scenario is examined for a case study of the greater Toronto, Ontario, Canada, area using data on current technology stocks and government projections for stock change. The scenario presented suggests that even with some aggressive targets for technological adoption (especially in the transportation sector), it will be difficult to achieve the less ambitious 2050 emissions reduction goals of the Intergovernmental Panel on Climate Change. This is largely attributable to the long life of the building stock and limitations of current retrofit practices. Additionally, demand reduction (through transportation mode shifting and building occupant behavior) will be an important component of future emissions cuts.

On estimation and influence diagnostics for the Grubbs` model under heavy-tailed distributions

The Grubbs` measurement model is frequently used to compare several measuring devices. It is common to assume that the random terms have a normal distribution. However, such assumption makes the inference vulnerable to outlying observations, whereas scale mixtures of normal distributions have been an interesting alternative to produce robust estimates, keeping the elegancy and simplicity of the maximum likelihood theory. The aim of this paper is to develop an EM-type algorithm for the parameter estimation, and to use the local influence method to assess the robustness aspects of these parameter estimates under some usual perturbation schemes, In order to identify outliers and to criticize the model building we use the local influence procedure in a Study to compare the precision of several thermocouples. (C) 2008 Elsevier B.V. All rights reserved.

Development of a PWR-W and an AP1000® containment building 3D model with a CFD code for Best-Estimate Thermal-Hydraulic Analysis

The simulation of design basis accidents in a containment building is usually conducted with a lumped parameter model. The codes normally used by Westinghouse Electric Company (WEC) for that license analysis are WGOTHIC or COCO, which are suitable to provide an adequate estimation of the overall peak temperature and pressure of the containment. However, for the detailed study of the thermal-hydraulic behavior in every room and compartment of the containment building, it could be more convenient to model the containment with a more detailed 3D representation of the geometry of the whole building. The main objective of this project is to obtain a standard PWR Westinghouse as well as an AP1000® containment model for a CFD code to analyze the thermal-hydraulic detailed behavior during a design basis accident. In this paper the development and testing of both containment models is presented.

Estimation of water retention curve from mercury intrusion porosimetry and van Genuchten model

The water retention curve (WRC) is a hydraulic characteristic of concrete required for advanced modeling of water (and thus solute) transport in variably saturated, heterogeneous concrete. Unfortunately, determination by a direct experimental method (for example, measuring equilibrium moisture levels of large samples stored in constant humidity cells) is a lengthy process, taking over 2 years for large samples. A surrogate approach is presented in which the WRC is conveniently estimated from mercury intrusion porosimetry (MIP) and validated by water sorption isotherms: The well-known Barrett, Joyner and Halenda (BJH) method of estimating the pore size distribution (PSD) from the water sorption isotherm is shown to complement the PSD derived from conventional MIP. This provides a basis for predicting the complete WRC from MIP data alone. The van Genuchten equation is used to model the combined water sorption and MIP results. It is a convenient tool for describing water retention characteristics over the full moisture content range. The van Genuchten parameter estimation based solely on MIP is shown to give a satisfactory approximation to the WRC, with a simple restriction on one. of the parameters.

Improved Annual Average Daily Traffic (AADT) estimation for local roads using parcel-level travel demand modeling

Annual Average Daily Traffic (AADT) is a critical input to many transportation analyses. By definition, AADT is the average 24-hour volume at a highway location over a full year. Traditionally, AADT is estimated using a mix of permanent and temporary traffic counts. Because field collection of traffic counts is expensive, it is usually done for only the major roads, thus leaving most of the local roads without any AADT information. However, AADTs are needed for local roads for many applications. For example, AADTs are used by state Departments of Transportation (DOTs) to calculate the crash rates of all local roads in order to identify the top five percent of hazardous locations for annual reporting to the U.S. DOT. ^ This dissertation develops a new method for estimating AADTs for local roads using travel demand modeling. A major component of the new method involves a parcel-level trip generation model that estimates the trips generated by each parcel. The model uses the tax parcel data together with the trip generation rates and equations provided by the ITE Trip Generation Report. The generated trips are then distributed to existing traffic count sites using a parcel-level trip distribution gravity model. The all-or-nothing assignment method is then used to assign the trips onto the roadway network to estimate the final AADTs. The entire process was implemented in the Cube demand modeling system with extensive spatial data processing using ArcGIS. ^ To evaluate the performance of the new method, data from several study areas in Broward County in Florida were used. The estimated AADTs were compared with those from two existing methods using actual traffic counts as the ground truths. The results show that the new method performs better than both existing methods. One limitation with the new method is that it relies on Cube which limits the number of zones to 32,000. Accordingly, a study area exceeding this limit must be partitioned into smaller areas. Because AADT estimates for roads near the boundary areas were found to be less accurate, further research could examine the best way to partition a study area to minimize the impact.^

Activity-based life cycle costing model for cost estimation and monitoring – Case: manned and autonomous dry bulk carrier

Recent developments in automation, robotics and artificial intelligence have given a push to a wider usage of these technologies in recent years, and nowadays, driverless transport systems are already state-of-the-art on certain legs of transportation. This has given a push for the maritime industry to join the advancement. The case organisation, AAWA initiative, is a joint industry-academia research consortium with the objective of developing readiness for the first commercial autonomous solutions, exploiting state-of-the-art autonomous and remote technology. The initiative develops both autonomous and remote operation technology for navigation, machinery, and all on-board operating systems. The aim of this study is to develop a model with which to estimate and forecast the operational costs, and thus enable comparisons between manned and autonomous cargo vessels. The building process of the model is also described and discussed. Furthermore, the model’s aim is to track and identify the critical success factors of the chosen ship design, and to enable monitoring and tracking of the incurred operational costs as the life cycle of the vessel progresses. The study adopts the constructive research approach, as the aim is to develop a construct to meet the needs of a case organisation. Data has been collected through discussions and meeting with consortium members and researchers, as well as through written and internal communications material. The model itself is built using activity-based life cycle costing, which enables both realistic cost estimation and forecasting, as well as the identification of critical success factors due to the process-orientation adopted from activity-based costing and the statistical nature of Monte Carlo simulation techniques. As the model was able to meet the multiple aims set for it, and the case organisation was satisfied with it, it could be argued that activity-based life cycle costing is the method with which to conduct cost estimation and forecasting in the case of autonomous cargo vessels. The model was able to perform the cost analysis and forecasting, as well as to trace the critical success factors. Later on, it also enabled, albeit hypothetically, monitoring and tracking of the incurred costs. By collecting costs this way, it was argued that the activity-based LCC model is able facilitate learning from and continuous improvement of the autonomous vessel. As with the building process of the model, an individual approach was chosen, while still using the implementation and model building steps presented in existing literature. This was due to two factors: the nature of the model and – perhaps even more importantly – the nature of the case organisation. Furthermore, the loosely organised network structure means that knowing the case organisation and its aims is of great importance when conducting a constructive research.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

Leaf area index estimation with MODIS reflectance time series and model inversion during full rotations of Eucalyptus plantations

The leaf area index (LAI) of fast-growing Eucalyptus plantations is highly dynamic both seasonally and interannually, and is spatially variable depending on pedo-climatic conditions. LAI is very important in determining the carbon and water balance of a stand, but is difficult to measure during a complete stand rotation and at large scales. Remote-sensing methods allowing the retrieval of LAI time series with accuracy and precision are therefore necessary. Here, we tested two methods for LAI estimation from MODIS 250m resolution red and near-infrared (NIR) reflectance time series. The first method involved the inversion of a coupled model of leaf reflectance and transmittance (PROSPECT4), soil reflectance (SOILSPECT) and canopy radiative transfer (4SAIL2). Model parameters other than the LAI were either fixed to measured constant values, or allowed to vary seasonally and/or with stand age according to trends observed in field measurements. The LAI was assumed to vary throughout the rotation following a series of alternately increasing and decreasing sigmoid curves. The parameters of each sigmoid curve that allowed the best fit of simulated canopy reflectance to MODIS red and NIR reflectance data were obtained by minimization techniques. The second method was based on a linear relationship between the LAI and values of the GEneralized Soil Adjusted Vegetation Index (GESAVI), which was calibrated using destructive LAI measurements made at two seasons, on Eucalyptus stands of different ages and productivity levels. The ability of each approach to reproduce field-measured LAI values was assessed, and uncertainty on results and parameter sensitivities were examined. Both methods offered a good fit between measured and estimated LAI (R(2) = 0.80 and R(2) = 0.62 for model inversion and GESAVI-based methods, respectively), but the GESAVI-based method overestimated the LAI at young ages. (C) 2010 Elsevier Inc. All rights reserved.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.