A holistic methodology for the non-destructive experimental characterization and reliability-based structural assessment of historical steel bridges

Financiado para publicación en acceso aberto: Universidade de Vigo/CISUGNowadays, several historical steel structures present damage and an advanced deterioration state induced by human or natural actions, causing fluctuations in geometrical, physical, and mechanical properties that dramatically affect their mechanical behavior. Due to the economic, cultural, and heritage value, these constructions must be comprehensively assessed to verify their current condition state. This work presents a holistic methodology aimed at the non-destructive experimental characterization and reliability-based structural assessment of historical steel bridges. It comprehends from the experimental data acquisition to the finite element model updating and the probabilistic-based structural assessment to obtain the reliability indexes of serviceability and ultimate limit states. Several sources of information are considered in the evaluation process, thus, results are more realistic and accurate and can be used for optimal decision-making related to maintenance and retrofitting actions. The feasibility of the methodology has been tested on O Barqueiro Bridge, an aging riveted bridge located in Galicia, Spain. The study first involved a comprehensive experimental campaign to characterize the bridge effectively at multiple levels: geometry, material, and structural system by the synergetic combination of different tools and methods: in-depth visual inspection, terrestrial laser scanner survey, ultrasonic testing, and ambient vibration test. Subsequently, a detailed FE model was developed and calibrated with an average relative error in frequencies of 2.04% and an average MAC value of 0.94. Finally, the reliability-based structural assessment was performed, yielding reliability indexes of 1.80 and 1.99 for the serviceability and ultimate limit states, respectively. Thus, the bridge could not withstand traffic loads with satisfactory structural performance in its current condition.Ministerio de Ciencia, Innovación y Universidades | Ref. RTI2018-095893-B-C21European Regional Development Fund | Ref. EAPA_826/201

Performance of Active Vibration Isolation in the Advanced LIGO Detectors

The second generation of LIGO detectors has finished construction and the commissioning effort is pushing the instruments towards their designed sensitivity. Around the world similar undertakings are underway, and soon a global network capable of astrophysical observation will be operational. The first sentences are being written in an important chapter of terrestrial gravitational wave detection, an entire century after the theoretical foundations of general relativity were laid, and after decades of calculation, design, proposals, plans, and laboratory work. In order to make sensitive measurements, the detector must be well isolated from the vibrations of the ground, and much of this thesis describes the effectiveness of active control platforms used to mitigate the transmission of seismic motions to the test masses. This work was performed both during the last science run of the first generation LIGO detector and as part of the commissioning of the second generation instrument

Investigation of Temperature Effects into Long-Span Bridges via Hybrid Sensing and Supervised Regression Models

Temperature is an important environmental factor for long-span bridges because it induces thermal loads on structural components that cause considerable displacements, stresses, and structural damage. Hence, it is critical to acquire up-to-date information on the status, sustainability, and serviceability of long-span bridges under daily and seasonal temperature fluctuations. This paper intends to investigate the effects of temperature variability on structural displacements obtained from remote sensing and represent their relationship using supervised regression models. In contrast to other studies in this field, one of the contributions of this paper is to leverage hybrid sensing as a combination of contact and non-contact sensors for measuring temperature data and structural responses. Apart from temperature, other unmeasured environmental and operational conditions may affect structural displacements of long-span bridges separately or simultaneously. For this issue, this paper incorporates a correlation analysis between the measured predictor (temperature) and response (displacement) data using a linear correlation measure, the Pearson correlation coefficient, as well as nonlinear correlation measures, namely the Spearman and Kendall correlation coefficients and the maximal information criterion, to determine whether the measured environmental factor is dominant or other unmeasured conditions affect structural responses. Finally, three supervised regression techniques based on a linear regression model, Gaussian process regression, and support vector regression are considered to model the relationship between temperature and structural displacements and to conduct the prediction process. Temperature and limited displacement data related to three long-span bridges are used to demonstrate the results of this research. The aim of this research is to assess and realize whether contact-based sensors installed in a bridge structure for measuring environmental and/or operational factors are sufficient or if it is necessary to consider further sensors and investigations

GelSight Baby Fin Ray: A Compact, Compliant, Flexible Finger with High-Resolution Tactile Sensing

The synthesis of tactile sensing with compliance is essential to many fields, from agricultural usages like fruit picking, to sustainability practices such as sorting recycling, to the creation of safe home-care robots for the elderly to age with dignity. From tactile sensing, we can discern material properties, recognize textures, and determine softness, while with compliance, we are able to securely and safely interact with the objects and the environment around us. These two abilities can culminate into a useful soft robotic gripper, such as the original GelSight Fin Ray, which is able to grasp a large variety of different objects and also perform a simple household manipulation task: wine glass reorientation. Although the original GelSight Fin Ray solves the problem of interfacing a generally rigid, high-resolution sensor with a soft, compliant structure, we can improve the robustness of the sensor and implement techniques that make such camera-based tactile sensors applicable to a wider variety of soft robot designs. We first integrate flexible mirrors and incorporate the rigid electronic components into the base of the gripper, which greatly improves the compliance of the Fin Ray structure. Then, we synthesize a flexible and high-elongation silicone adhesive-based fluorescent paint, which can provide good quality 2D tactile localization results for our sensor. Finally, we incorporate all of these techniques into a new design: the Baby Fin Ray, which we use to dig through clutter, and perform successful classification of nuts in their shells. The supplementary video can be found here: https://youtu.be/_oD_QFtYTPMComment: Accepted to IEEE Conference of Soft Robotics (RoboSoft) 202

Flow structure of low-density gas jets and gas jet diffusion flames.

Buoyant jets and flames have been a subject of significant research in fluid dynamics. Such flows are influenced by near field instabilities, turbulence, buoyancy, chemistry, heat release, etc. The present research deals with computational and experimental studies to improve understanding of laminar-turbulent jets and flames.As a first step, computational analysis of the near-field flow structure in an isothermal helium jet injected into quiescent ambient air environment was conducted. The jet Reynolds number, Re was varied from 40 to 150 to encompass steady and oscillating jet flow regimes. At low jet Reynolds numbers, the flow was steady and the concentration shear layer at the tube exit was stratified by mixing between jet and ambient fluids inside the tube. At higher jet Reynolds numbers (Re = 90 and 150), buoyancy induced acceleration contracted the jet core to form a toroidal vortex by entrainment of the ambient fluid. Next, the effects of buoyancy on buoyant and inertial low-density gas jets were studied by initiating computations in Earth gravity and subsequently, reducing the gravity to simulate microgravity conditions in the 2.2 s drop tower.As a successive step towards development of advanced optical diagnostic systems for measuring fluid flow phenomena in small scale turbulent structures, a miniature rainbow schlieren deflectometry system to non-intrusively measure species concentration and temperature data across the whole field was developed. The capability of the system was demonstrated by obtaining concentration measurements in a helium micro-jet (diameter, d = 650 mum) and temperature and concentration measurements in a hydrogen jet diffusion flame from a micro-injector (d = 50 mum). Finally, the flow field of under-expanded nitrogen jets was visualized to reveal details of the shock structures existing downstream of the jet exit.From an experimental perspective, in order to facilitate turbulence measurements, a crossbeam rainbow schlieren deflectometry system was developed and demonstrated by presenting schlieren visualizations of turbulent jets and flames. Subsequently, the theoretical framework of the crossbeam correlation technique requiring assumptions of homogeneous and isotropic turbulence was presented. The validity of the technique was also verified using laminar and turbulent data generated synthetically. The limitations of the technique were also discussed

Thermal error modelling of a gantry-type 5-axis machine tool using a Grey Neural Network Model

This paper presents a new modelling methodology for compensation of the thermal errors on a gantry-type 5-axis CNC machine tool. The method uses a “Grey Neural Network Model with Convolution Integral” (GNNMCI(1, N)), which makes full use of the similarities and complementarity between Grey system models and artificial neural networks (ANNs) to overcome the disadvantage of applying either model in isolation. A Particle Swarm Optimisation (PSO) algorithm is also employed to optimise the proposed Grey neural network. The size of the data pairs is crucial when the generation of data is a costly affair, since the machine downtime necessary to acquire the data is often considered prohibitive. Under such circumstances, optimisation of the number of data pairs used for training is of prime concern for calibrating a physical model or training a black-box model. A Grey Accumulated Generating Operation (AGO), which is a basis of the Grey system theory, is used to transform the original data to a monotonic series of data, which has less randomness than the original series of data. The choice of inputs to the thermal model is a non-trivial decision which is ultimately a compromise between the ability to obtain data that sufficiently correlates with the thermal distortion and the cost of implementation of the necessary feedback sensors. In this study, temperature measurement at key locations was supplemented by direct distortion measurement at accessible locations. This form of data fusion simplifies the modelling process, enhances the accuracy of the system and reduces the overall number of inputs to the model, since otherwise a much larger number of thermal sensors would be required to cover the entire structure. The Z-axis heating test, C-axis heating test, and the combined (helical) movement are considered in this work. The compensation values, calculated by the GNNMCI(1, N) model were sent to the controller for live error compensation. Test results show that a 85% reduction in thermal errors was achieved after compensation

External Tank Program Legacy of Success

I.Goal: a) Extensive TPS damage caused by extreme hail storm. b) Repair plan required to restore TPS to minimize program manifest impacts. II. Challenges: a) Skeptical technical community - Concerned about interactions of damage with known/unknown failure modes. b) Schedule pressure to accommodate ISS program- Next tank still at MAF c)Limited ET resources. III. How d We Do It?: a) Developed unique engineering requirements and tooling to minimize repairs. b) Performed large amount of performance testing to demonstrate understanding of repairs and residual conditions. c) Effectively communicated results to technical community and management to instill confidence in expected performance

Pancreas robot

Master of ScienceDepartment of Biological & Agricultural EngineeringDaniel FlippoThe World continues to need increased production of food to sustain the expected population growth over the next 30 years. The global population is projected to be more than 9.7 billion people by 2050. These people will need to eat nearly double the amount of food that is produced today. There are many approaches to solving this food crisis dilemma and progress is being made on multiple fronts. Sources of production growth include larger and more precise machine technology; more robust fertilizer applications; and crop modeling for genetically enhanced phenotyping. This paper focuses on the use of robotic technology to help model crop growth by using an unmanned ground vehicle (UGV) for data collection. Simple crop modeling helped the agricultural revolution in the 20th century. Today, scientists are building upon those models to create more complex ways to represent crops and their traits. These models require large amounts of data to observe and describe relationships between inputs and crop responses. This data needs to be dependable, consistent, and as close to the source as possible. To achieve that type of data for this project, a UGV was developed to traverse rugged field conditions. The UGV was designed to carry a Geophex Electromagnetic (EM) sensor that measures the electrical conductivity of the soil. This electrical conductivity will be used to decipher soil characteristics that underlie the growth potential of different wheat traits. The robot that carries the EM sensor must be designed to not interfere with the conductivity measurements of the sensor. The data collected must be accurate and repeatable. The scope of this research project is to develop the UGV to carry the sensor through the harsh field environments while not interfering with the incoming EM signal from the sensor. The project also explores methods for the robot to navigate through its environment on its own to limit human influence on the recorded data

Development of an ultrafast laser ultra-precision machining platform

Ultra-precision manufacturing is commonplace in today’s society. It is used in a huge number of applications from electronics, medical devices to energy devices. Most devices manufactured using ultra-precision methods are made in high quantities where the volume of the components is required to outweigh the cost of the production equipment. However, there are few technologies targeting the manufacture of prototypes or small batches and those that are costly in terms of time or resources. Thus, there is a demand for a high speed, flexible manufacturing platform that is capable of ultra-precise manufacture. Currently, manufacturing techniques using ultrafast lasers are limited with regards to accuracy and repeatability. This body of work investigates how to develop an ultra-precision ultrafast laser manufacturing platform. From literature it was found that there are a significant number of avenues that could be investigated to improve the precision of an ultrafast laser machining process. This included the integration of metrology to perform closed-loop processing, studies of laser stability, new machining strategies and the effect of processing on plume formation. A significant proportion of the research presented was focused on the development of the ultra-precision platform. This work was carried out to provide a basis for this research but also for those that will use the platform in the future. One of the key outputs from this development was a graphical user interface that integrated with the range of devices on the platform such as the laser, 5-axis stage and beam diagnostic tools. This interface provides methods for automatic tilt correction, autofocus for the laser, angular ablation machining methods and other diagnostic tools. The interface is setup to capture the required data to provide traceability and diagnostics on the laser machining process. This aided the research carried out into improving the accuracy and repeatability of the laser-based process. First, an investigation into the characteristics of the laser installed on the ultra-precision platform was undertaken to determine the long-term stability of the laser with regards to the pointing stability, power stability and beam diameter stability. These characteristics are significant because they all affect the fluence at the focal spot which is responsible for ablating material. Variance in any of those parameters can have an effect and therefore influence the accuracy and repeatability of the process. The effect of duty cycle on power repeatability and the implications of this on machining was examined. Finally, a simulation was created to demonstrate the effect of laser stability on quality of machining. The ability to machine on angled planes enabled an investigation of the effect of angle on plume formation and the ablation threshold of the material. The ablation threshold for silicon was found at angles between normal and 45 degrees. It was found that the threshold could not be correlated with change of incident angle on the area of the focal spot. A range of different powers and angles were captured using the holographic camera and the effect on plume development was assessed. Overall, a range of tasks was completed which enabled several developments of the ultra-precision platform. These included in-process monitoring, the establishment of a novel machining strategy, and the capture of the effect of angular ablation on plume formation using a holographic camera. The platform is now placed to continue further development and integrate with other metrology technologies to provide closed-loop machining capabilities which will lead into a laser-based process which will be used for MEMS and similar device manufacture.EPSR