Thin-Walled Cylindrical Shell Storage Tank under Blast Impacts: Finite Element Analysis

Thin-walled cylindrical shell storage tanks are pressure vessels in which the walls of the vessel have a thickness that is much smaller than the overall size of the vessel. These types of structures have global applications in various industries, including oil refineries and petrochemical plants. However, these storage tanks are vulnerable to fire and explosions. Therefore, a parametric study using numerical simulation was carried out, considering the internal liquid level, wall thickness, material yield strength, constraint conditions, and blast intensity, with a diameter of 100 m and height of 22.5 m under different blast loads using the finite element analysis method. The thickness of the tank wall is varied as 10 mm, 20 mm, 30 mm, and 40 mm, while the fill level of internal fluid is varied as 25, 50, 75, and 100%. The blast simulation was conducted using LS-DYNA software. The numerical results are then compared with analytical results. The effects of blast intensity, standoff distance, wall thickness, and fill level of internal fluid on the structural behaviour of the storage tank were investigated and discussed.

Capabilities and Limitations of Telematics for Vehicle Emissions Inventories

Eastern Research Group, Inc. evaluated the current state of personal vehicle telematics data with respect to emission inventory development, identifying relative strengths and weaknesses, and how these data could align better with the needs of emission modelers. A market survey of telematics firms provided an overview of available data, and identified several candidate sources for location-based and engine-based telematics data on personal vehicles. Data were then purchased from three different vendors: StreetLight Data, Moonshadow Mobile, and Otonomo. These data were applied in case studies conducted in the Denver metro area, U.S., to assess strengths and weaknesses of telematics for developing emission inventories. Case studies included using telematics to estimate regional vehicle miles traveled (VMT) for annual emission inventories; tracking the VMT impacts of COVID shutdown; generating location- and time-specific vehicle activity inputs for project scale “hot spot” air quality analysis; and estimating the distribution of fuel fill level from real-world data, which is important for evaporative emissions. These case studies confirmed that telematics can serve a growing range of emission inventory use cases, and use of these data may help improve emission inventory accuracy. However, there are also several limitations of the data to consider in preparing emission inventories; for example, it can be difficult to assess the representativeness of telematics data because of a lack of vehicle information. The authors encourage telematics firms to cater data products more directly to the needs of emission inventory modelers, to better harness the enormous potential of these data for refining vehicle emission inventory estimates.

Impact of Bone Augmentation of Facial Bone Defect around Osseointegrated Implant: A Three Dimensional Finite Element Analysis

(1) Background: When dental implants are placed at the esthetic zone, facial bone fenestration might be expected. This study aimed to evaluate the biomechanical effect of bone augmentation around implants with facial bone fenestration defects using the finite element method. (2) Methods: An anterior maxillary region model with facial concavity was constructed with a threaded implant inserted following the root direction, resulting in apical threads exposure to represent the fenestration model. Several bone coverage levels were simulated by gradually shifting the deepest concavity point buccally, mimicking bone augmentation surgeries with different bone fill results. Oblique forces were applied, and analysis was performed. (3) Results: Peak compressive stress magnitude and distribution varied according to the level of exposure and facial concavity depth. The fenestration model demonstrated a slightly lower peak peri-implant bone stress, smaller implant displacement, and smaller bone volume with strain levels above 200 µ strain. A gradual increase in compressive stress, implant displacement, and bone volume exhibited strain level above 200 µ strain was observed with the increased bone fill level of the facial bone fenestration. (4) Conclusions: Exposure of implants apical threads at the maxillary anterior region does not significantly affect the peri-implant stress and strain results. However, increasing the buccolingual width and eliminating the buccal concavity might increase the peri-implant bone volume exhibited favorable loading levels.

Mixing Assessment of Non-Cohesive Mono-disperse and Bi-disperse Particles in a Paddle Mixer – Experiments and Discrete Element Method (DEM) Application

The objective of this study was to assess the mixing performance of a horizontal paddle blender for mono-disperse and bi-disperse particles. The assessment was performed through the application of the Discrete Element Method (DEM) simulations, experiments, and Analysis of Variance (ANOVA). EDEM 2.7 commercial software was utilized for the mono-disperse simulations while LIGGGHTS(R)-PUBLIC 3.3.1, an open source software, was used for the bi-disperse simulations. DEM models were validated with experimental data. Simulations were performed to explore the effect of impeller rotational speed, vessel fill level, particle number composition, and particle loading arrangement on mixing quality defined by the Relative Standard Deviation (RSD) index. The flow pattern and mixing mechanisms were examined through granular temperature, particle diffusivity, and Peclet number. The impeller rotational speed was the most influential parameter on the mixing performance of mono-disperse particles. The particle number composition was the dominating parameter on the mixing quality of bi-disperse particles

Mixing Assessment of Non-Cohesive Mono-disperse and Bi-disperse Particles in a Paddle Mixer – Experiments and Discrete Element Method (DEM) Application

The objective of this study was to assess the mixing performance of a horizontal paddle blender for mono-disperse and bi-disperse particles. The assessment was performed through the application of the Discrete Element Method (DEM) simulations, experiments, and Analysis of Variance (ANOVA). EDEM 2.7 commercial software was utilized for the mono-disperse simulations while LIGGGHTS(R)-PUBLIC 3.3.1, an open source software, was used for the bi-disperse simulations. DEM models were validated with experimental data. Simulations were performed to explore the effect of impeller rotational speed, vessel fill level, particle number composition, and particle loading arrangement on mixing quality defined by the Relative Standard Deviation (RSD) index. The flow pattern and mixing mechanisms were examined through granular temperature, particle diffusivity, and Peclet number. The impeller rotational speed was the most influential parameter on the mixing performance of mono-disperse particles. The particle number composition was the dominating parameter on the mixing quality of bi-disperse particles

Analysis of the mixing of solid particles in the slant cone and ploughshare mixers via Discrete Element Method (DEM)

Discrete element method (DEM) was employed to characterize the mixing of the solid particles in two different types of the powder blenders. In the first part of this study, DEM was used to investigate the effects of initial loading, drum speed, fill level, and agitator speed on the mixing efficiency of a slant cone mixer. DEM simulation results were in good agreement with the experimentally determined data, both qualitatively and quantitatively. In the second part of this study, DEM was employed to characterize the mixing of the solid particles in a Ploughshare mixer. To validate the model, the simulation results were compared to the positron emission particle tracking (PEPT) data reported in the literature. The validated DEM was then utilized to calculate the mixing index as a function of the initial loading, plough rotational speed, fill level, and particle size for a ploughshare mixer.

Analysis of the mixing of solid particles in the slant cone and ploughshare mixers via Discrete Element Method (DEM)

Discrete element method (DEM) was employed to characterize the mixing of the solid particles in two different types of the powder blenders. In the first part of this study, DEM was used to investigate the effects of initial loading, drum speed, fill level, and agitator speed on the mixing efficiency of a slant cone mixer. DEM simulation results were in good agreement with the experimentally determined data, both qualitatively and quantitatively. In the second part of this study, DEM was employed to characterize the mixing of the solid particles in a Ploughshare mixer. To validate the model, the simulation results were compared to the positron emission particle tracking (PEPT) data reported in the literature. The validated DEM was then utilized to calculate the mixing index as a function of the initial loading, plough rotational speed, fill level, and particle size for a ploughshare mixer.

Dynamic water fill level measurement using a phantom-dependent adaptive electrical capacitance tomography (ECT) method

In electrical capacitance tomography (ECT), the resolution of the reconstructed permittivity distribution improves with the number of electrodes used whereas the number of capacitance measurements and the measurement time increases with the number of electrodes. To cope with this tradeoff, we present a phantom-dependent adaptation scheme in which coarse measurements are performed with terminal electrodes interconnected to form a synthetic electrode ring with fewer but larger electrodes. The concept was tested by observing the sloshing of water inside a pipe. We compare the reconstructed results based on eight synthetic electrodes, on 16 elementary electrodes, and on the adaptation scheme involving both the eight synthetic electrodes and some of the elementary capacitances. The reconstruction used the projected Landweber algorithm for capacitances determined by a finite-element simulation and for measured capacitances. The results contain artefacts attributed to the influence of the high permittivity of water compared to the low permittivity of the pipe wall. The adaptation scheme leads to nearly the same information as a full measurement of all 120 elementary capacitances but only requires the measurement of 30 % fewer capacitances. By detecting the fill level using a tomometric method, it can be determined within an uncertainty of 5 % FS.