Fatigue assessment of welded joints using finite element methods is becoming very common. Research about new methods is being carried out every day that show a more accurate estimation of the fatigue life cycle than the previous ones. Some of these methods are investigated in this thesis for a thorough understanding of the weld fatigue evaluation process.The thesis study presents several methods as candidates for analysis of selected case studies for comparison. The sensitivity of methods towards FE model properties was studied. The ease of implementation for further automatization of the method was highly considered from the early stages of the project. A comparison study amongst feasible methods was then performed after analysis.The selected three case studies provided a wide range of difficulties in terms of geometry and loading and made them suitable for the methods to be evaluated. It should be noted that case studies only with fillet welds were considered during the literature study and analysis. Implementation of some methods on a case study where they have not previously been tested before gave a challenging task during the analysis phase. The proposed method after comparison and ranking of the methods based on several criteria such as accuracy, robustness, etc. was the hot spot stress method. The main advantages of this method are its low computational time, less complexity during both pre- and post-processing, and the ability to work for both solid and shell models.Finally, the report gives a walk-through of several functionalities of the post-processor tool built to enhance workflow for the hot spot based fatigue assessment of welds. Pseudo-codes for some functions of the tool are given for clarity. A summary of the workflow is presented as a flowchart. The outputs of the case studies were then evaluated using the tool and compared with the manual evaluation to check the effectiveness of the tool on different scenarios. The tool shows flexibility in handling different types of weld geometry with good agreement to the results obtained manually but only for welds lying on a flat surface. Some of the advantages of the tool are its capability to handle multiple welds simultaneously and the flexibility to the user in selecting the way the results are presented. Most of the postprocessing steps are automatized, while some require user inputs.

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Industry 4.0 will pave the way to a new age of advanced manufacturing. Additive manufacturing (AM) is one of the leading sectors of the upcoming industrial revolution. The key advantage of AM is its ability to generate lightweight, robust, and complex shapes. AM can also customize the microstructure and mechanical properties of the components according to the selected technique and process parameters. AM of metals using selective laser melting (SLM) could significantly impact a variety of critical applications. SLM is the most common technique of processing high strength Aluminum alloys. SLM of these alloys promises to enhance the performance of lightweight critical components used in various aerospace and automotive applications such as metallic optics and optomechanical components. However, the surface and inside defects of the as-built parts present an obstacle to product quality requirements. Consequently, the post-processing of SLM produced Al alloy parts is an essential step for homogenizing their microstructure and reducing as-built defects. In the current research, various studies assess the optimal process mapping for high-quality SLM parts and the post-processing treatment of Al alloy parts. Ultra-precision machining with single point diamond turning or diamond micro fly-milling is also investigated for the as-built and post-processed Al parts to satisfy the optical mirror’s surface finish requirements. The influence of the SLM process parameters on the quality of the AlSi10Mg and Al6061 alloy parts is investigated. A design of experiment (DOE) is used to analyze relative density, porosity, surface roughness, dimensional accuracy, and mechanical properties according to the interaction effect between SLM process parameters. The microstructure of both materials was also characterized. A developed process map shows the range of energy densities and SLM process parameters for each material needed to achieve optimum quality of the as-built parts. This comprehensive study also strives to reduce the amount of post-processing needed. Thermal post-processing of AlSi10Mg parts is evaluated, using recycled powder, with the aim of improving the microstructure homogeneity of the as-built parts. This work is essential for the cost-effective additive manufacturing (AM) of metal optics and optomechanical systems. To achieve this goal, a full characterization of fresh and recycled powder was performed, in addition to a microstructure assessment of the as-built fabricated samples. Annealing, solution heat treatment (SHT) and T6 heat treatment (T6 HT) were applied under different processing conditions. The results demonstrated an improvement in microstructure homogeneity after thermal post-processing under specific conditions of SHT and T6 HT. A micro-hardness map was developed to help in the selection of optimal post-processing parameters for the part’s design requirements. A study is also presented, which aims to improve the surface characteristics of the as-built AlSi10Mg parts using shot peening (SP). Different SP intensities were applied to various surface textures of the as-built samples. The SP results showed a significant improvement in the as-built surface topography and a higher value of effective depth using 22.9A intensity and Gp165 glass beads. The area near the shot-peened surface showed a significant microstructure refinement up to a specific depth, due to the dynamic precipitation of nanoscale Si particles. Surface hardening and high compressive residual stresses were generated due to severe plastic deformation. Friction stir processing (FSP) was studied as a localized treatment on a large surface area of the as-built and hot isostatic pressed (HIPed) AlSi10Mg parts using multiple FSP tool passes. The influence of FSP on the microstructure, hardness, and residual stresses of parts was investigated. FSP transforms the microstructure of parts into an equiaxed grain structure. A consistent microstructure homogenization was achieved over the processed surface after applying a high ratio of tool pass overlap of ≥60%. A map of microstructure and hardness was prepared to assist in the selection of the optimal FSP parameters for attaining the required quality of the final processed parts. Micromachining to the mirror surface was performed using diamond micro fly-milling and single point diamond turning techniques, and the effect of the material properties on surface roughness after machining was investigated. The machining parameters were also tuned to meet IR mirror optical requirements. A novel mirror structure is developed using the design for additive manufacturing concept additive (DFAM). This design achieved weight reduction of 50% as compared to the typical mirror structure. Moreover, the developed design offers an improvement of the mirror cooling performance due to the embedded cooling channels directed to the mirror surface. A novel mirror structure is developed using the design for additive manufacturing concept additive (DFAM). This design achieved weight reduction of 50% as compared to the typical mirror structure. Moreover, the developed design offers an improvement of the mirror cooling performance due to the embedded cooling channels directed to the mirror surface. / Thesis / Doctor of Philosophy (PhD)

The number of flood events and the estimated costs of floods have increased dramatically over the past few decades. To reduce the negative impacts of flooding, reliable flood forecasting is essential for early warning and decision making. Although various flood forecasting models and techniques have been developed, the assessment and reduction of uncertainties associated with the forecast remain a challenging task. Therefore, this thesis focuses on the investigation of Bayesian methods for producing probabilistic flood forecasts to accurately quantify predictive uncertainty and enhance the forecast performance and reliability. In the thesis, hydrologic uncertainty was quantified by a Bayesian post-processor - Hydrologic Uncertainty Processor (HUP), and the predictability of HUP with different hydrologic models under different flow conditions were investigated. Followed by an extension of HUP into an ensemble prediction framework, which constitutes the Bayesian Ensemble Uncertainty Processor (BEUP). Then the BEUP with bias-corrected ensemble weather inputs was tested to improve predictive performance. In addition, the effects of input and model type on BEUP were investigated through different combinations of BEUP with deterministic/ensemble weather predictions and lumped/semi-distributed hydrologic models. Results indicate that Bayesian method is robust for probabilistic flood forecasting with uncertainty assessment. HUP is able to improve the deterministic forecast from the hydrologic model and produces more accurate probabilistic forecast. Under high flow condition, a better performing hydrologic model yields better probabilistic forecast after applying HUP. BEUP can significantly improve the accuracy and reliability of short-range flood forecasts, but the improvement becomes less obvious as lead time increases. The best results for short-range forecasts are obtained by applying both bias correction and BEUP. Results also show that bias correcting each ensemble member of weather inputs generates better flood forecast than only bias correcting the ensemble mean. The improvement on BEUP brought by the hydrologic model type is more significant than the input data type. BEUP with semi-distributed model is recommended for short-range flood forecasts. / Dissertation / Doctor of Philosophy (PhD) / Flood is one of the top weather related hazards and causes serious property damage and loss of lives every year worldwide. If the timing and magnitude of the flood event could be accurately predicted in advance, it will allow time to get well prepared, and thus reduce its negative impacts. This research focuses on improving flood forecasts through advanced Bayesian techniques. The main objectives are: (1) enhancing reliability and accuracy of flood forecasting system; and (2) improving the assessment of predictive uncertainty associated with the flood forecasts. The key contributions include: (1) application of Bayesian forecasting methods in a semi-urban watershed to advance the predictive uncertainty quantification; and (2) investigation of the Bayesian forecasting methods with different inputs and models and combining bias correction technique to further improve the forecast performance. It is expected that the findings from this research will benefit flood impact mitigation, watershed management and water resources planning.

In the past two decades, the number of observations and the accuracy of satellite-basedgeodetic measurements like Global Navigation satellite systems (GNSS) greatly increased,providing measured values of displacements and velocities of permanent geodetic stations.Establishment of the geodetic control networks and collecting geodetic observations, indifferent epochs, are a commonly used method for detection of displacements andconsequently disaster management. Selecting proper processing parameters for differenttypes of monitoring networks are critical factors of the deformation monitoring analysisusing GNSS, which is the main aim of this research. In this study, a simulation study and acontrolled survey were performed using simultaneous GNSS measurements of 5 geodeticpillars, established by Lantmäteriet at Gävle airport. Sensitivity analyses were performed ondifferent types of monitoring networks using different set of processing paarameters . Thesescenarios consider different sets of parameters, different types of monitoring networks, andvarious number of monitoring stations to evaluate the detectable displacements andcompare with the known millimeter displacements (simulated one). The results showed thatthe selection of processing parameters depends on the type and size of the monitoringnetwork and the location of the monitoring stations. Analyses also show that onlineprocessing services can provide mm-cm level accuracy for displacement detection ifsufficient observation time is available. Finally, checks were performed on the two ofsample scenarios to find the minimum observation time required for reaching to the mostaccurate simulated (preset) displacements.

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / One of the requirements resulting from mounting pressure on flight test schedules is the reduction of time needed for data analysis, in pursuit of shorter test cycles. This requirement has ramifications such as the demand for record and processing of not just raw measurement data but also of data converted to engineering units in real time, as well as for an optimized use of the bandwidth available for telemetry downlink and ultimately for shortening the duration of procedures intended to disseminate pre-selected recorded data among different analysis groups on ground. A promising way to successfully address these needs consists in implementing more CPU-intelligence and processing power directly on the on-board flight test equipment. This provides the ability to process complex data in real time. For instance, data acquired at different hardware interfaces (which may be compliant with different standards) can be directly converted to more easy-to-handle engineering units. This leads to a faster extraction and analysis of the actual data contents of the on-board signals and busses. Another central goal is the efficient use of the available bandwidth for telemetry. Real-time data reduction via intelligent filtering is one approach to achieve this challenging objective. The data filtering process should be performed simultaneously on an all-data-capture recording and the user should be able to easily select the interesting data without building PCM formats on board nor to carry out decommutation on ground. This data selection should be as easy as possible for the user, and the on-board FTI devices should generate a seamless and transparent data transmission, making a quick data analysis viable. On-board data processing and filtering has the potential to become the future main path to handle the challenge of FTI data acquisition and analysis in a more comfortable and effective way.

This presentation is intended to inform about the enhancements to Creo Simulate 4.0 and the Roadmap for the future (5.0 +)

This presentation is intended to inform about the enhancements of Creo Simulate and the Roadmap for the future.

Este trabalho apresenta uma metodologia capaz de unir a análise hidrodinâmica de um sistema oceânico com sua análise estrutural, assim como o pós-processamento acoplado dos resultados. Foram criadas rotinas e códigos para que a série temporal de forças das linhas de risers e amarração de uma plataforma pudessem tornar-se dados passíveis de entrada num pré- processador de elementos finitos. Com a aplicação destas no modelo, e sua conseqüente análise no domínio do tempo, foi criada uma interface para os resultados do solver, para que pudesse ser importados no pós-processador hidrodinâmico, e visualizados com os mesmos movimentos que os obtidos na resposta da análise hidrodinâmica. O TPNView, atual pós-processador do laboratório Tanque de Provas Numérico(TPN), foi quem recebeu por fim as rotinas e interfaces criadas a partir das idéias apresentadas nesta dissertação. Com isso é possível ver em uma única ferramenta de visualização tanto o comportamento hidrodinâmico quanto o estrutural de uma estrutura do sistema de uma só vez.. / This work presents a methodology developed to treat the hydrodynamic analysis of an offshore system conjointly with its structural analysis; the same methodology also allows for combined post-processing of data. Programming routines were created so as to enable the use of the time series of the forces present at the risers and mooring lines as input data for a finite element analysis solver software. Applying this forces in to the finite element model, and its subsequent analysis in time domain, it was possible to create an interface between the solver output, so that structural analysis could be imported into the hydrodynamic post-processor and visualised with the same movements obtained in the hydrodynamic analysis response. TPNView, the post-processor developed at the Tanque de Provas Numérico laboratory, was benefited from the programming routines and interfaces developed for this thesis. Using the aforedescribed visualisation tools, it became possible to monitor at once both the hydrodynamic and the structural behaviour of a system component.