Abstract Garlid et al. [1] previously showed that it is feasible to determine marine riser disconnect criteria for a mobile offshore drilling unit (MODU) using the structural reliability analysis (SRA) method. The method was presented through a case study of a notional MODU moored, with static thruster assist, in shallow water and subjected to harsh environments. The case study was performed with a series of simplifications that might introduce unwanted conservatism for the end user, such as co-linear environmental forces and static thruster settings. Further, only ten environmental load cases were used to populate the response surfaces, leading to a relatively coarse response surface grid. Still, many time domain (TD) analyses were needed to populate the response surfaces that describe the relevant short-term response statistics. Although more computationally expensive, the SRA method offers several advantages over the conventional frequency-domain method currently employed in the industry. These advantages include the possibility of considering non-linear effects more accurately when considering extreme responses and the possibility of considering the coupling effects between the different components, such as the MODU and marine riser. Therefore, the SRA method is more accurate, allowing operators to run more efficient marine operations and possibly extending operational windows. In this paper, the authors will develop the SRA method further by utilizing active learning when performing the response surface generation to significantly reduce computational efforts. This paper will use the Kriging model to model the response surface. Stochastic noise in the sampling points is included in the model to avoid potential over-fitting. A significant reduction in analysis effort could make the SRA method closer in performance in terms of computational efforts against the conventional frequency domain, but with the added advantages of a high-fidelity method that can consider full-coupling and non-linear effects.
With the development of design level and construction technology of cable supported system, various new-type prestressed structures emerge, and a number of public buildings with cable dome structure have been constructed. The structural characteristics and complete set construction technology of Chengdu Phoenix Mountain Stadium are introduced in this paper. In view of the construction difficulties, nonlinear dynamic analysis method was used to carry out simulation of the whole construction process and optimize the construction scheme. The research was carried out from the aspects of rotary lifting technology, horizontal restraint system and high anti-side lifting frame group. Besides, the design and construction integrated analysis of the large opening cable dome structure was carried out, and the construction technology of " internal tension ring-cable net integrated lifting " was innovatively proposed. This method fills the blank of the construction method of the system, greatly improves the construction efficiency, and ensures the construction quality and safety.
Transient events cause high loads in the drivetrain components so measuring and calculating these loads can improve confidence in drivetrain design. This paper studies the Gearbox Reliability Collaborative 750kW wind turbine gearbox response during transient events using a combined experimental and modeling approach. The transient events include emergency shut-downs and start-ups measured during a field testing period in 2009. The drivetrain model is established in the multibody simulation tool Simpack. A detailed study of modeling fidelity required for accurate load prediction is performed and results are compared against measured loads. A high fidelity model that includes shaft and housing flexibility and accurate bearing stiffnesses is important for the higher-speed stage bearing loads. Each of the transient events has different modeling requirements.
Abstract Background To estimate cardiovascular and cancer death rates by regions and time periods. Design Novel statistical methods were used to analyze clinical surveillance data. Methods A multicenter, population‐based medical survey was performed. Annual recorded deaths from cardiovascular diseases were analyzed for all 195 countries of the world. It is challenging to model such data; few mathematical models can be applied because cardiovascular disease and cancer data are generally not normally distributed. Results A novel approach to assessing the biosystem reliability is introduced and has been found to be particularly suitable for analyzing multiregion environmental and healthcare systems. While traditional methods for analyzing temporal observations of multiregion processes do not deal with dimensionality efficiently, our methodology has been shown to be able to cope with this challenge. Conclusions Our novel methodology can be applied to public health and clinical survey data.
Background Novel coronavirus disease has been recently a concern for worldwide public health. To determine epidemic rate probability at any time in any region of interest, one needs efficient bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of novel coronavirus infection rate. Traditional statistical methods dealing with temporal observations of multi-regional processes do not have the multi-dimensionality advantage, that suggested methodology offers, namely dealing efficiently with multiple regions at the same time and accounting for cross-correlations between different regional observations. Methods Modern multi-dimensional novel statistical method was directly applied to raw clinical data, able to deal with territorial mapping. Novel reliability method based on statistical extreme value theory has been suggested to deal with challenging epidemic forecast. Authors used MATLAB optimization software. Results This paper described a novel bio-system reliability approach, particularly suitable for multi-country environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of extreme novel coronavirus death rate probability. Namely, accurate maximum recorded patient numbers are predicted for the years to come for the analyzed provinces. Conclusions The suggested method performed well by supplying not only an estimate but 95% confidence interval as well. Note that suggested methodology is not limited to any specific epidemics or any specific terrain, namely its truly general. The only assumption and limitation is bio-system stationarity, alternatively trend analysis should be performed first. The suggested methodology can be used in various public health applications, based on their clinical survey data.
This investigation maximize the annual energy production (AEP) of a wind farm’s layout at a specific site using a novel multi-stage approach. The downstream wind turbines’ energy production decreases due to the reduced wind speed and turbulence created by the upstream wind turbines’ wakes. The wake interference from wind turbines causes the reduction of overall power efficiency. This paper provides a novel multi-stage strategy for the optimal layouts generated by heuristic algorithms to address this problem. A comparison of the proposed multi-stage approach to previous optimization algorithms is presented to demonstrate its efficiency using three referenced cases and one potential wind farm in the Gulf of Maine. The results demonstrate that applying the proposed multi-stage approach increases AEP and decreases computational time compared to previous research and optimization algorithms, which is crucial for large-scale offshore wind farm layout design and optimization.
Abstract This paper presents the burst pressure design of the cargo tank used in the University of Stavanger (UiS) Subsea Freight-Glider (USFG). The USFG is an innovative large underwater cargo glider drone that is 50 m long and has a DWT of 1500 ton. It uses variable-buoyancy propulsion instead of traditional propellers for movement. This is an extremely efficient propulsion method and allows the USFG to achieve an average energy consumption of less than 10 kW. Structural weight is a premium as the USFG is required to be neutrally buoyant in water. Therefore, the design of the cargo tank which is the largest component in the USFG needs to be optimal for minimal structural weight. One approach used in design optimisation is to utilise design codes and/or methods that are more precise and therefore allow for lower safety margins. This approach will be investigated in this paper for the burst pressure design of the cargo tank. The different parts of ASME BPVC codes will be compared. The sensitivity of the codes to changes in design parameters is also investigated. Lastly, some comments on the use of reliability methods to further optimise the design are also presented.
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