Coupled simulation of loading and response of columns under extreme events

Forces imparted to structural columns during blast-induced loading depends on the shape and size of columns as well as on the intensity of the blast. Column\u27s geometry - i.e., shape and size - influences the flow field around the column and consequently the flow field determines forces experienced by the column The main objective of this research is to estimate the forces imparted to columns in a blast event through studying the air flow field around columns In this study, the physics of shock wave reflection and rarefaction waves are reviewed with application to describing the air flow around columns with circular and square cross sections. Then, simulations will be performed to determine the flow field around columns with different geometries. Based on the simulation results, force and impulse experienced by columns with different cross-sectional shapes and varying sizes are estimated. Finally, through curve-fitting techniques, correlations of variables are investigated and proper equations are proposed to estimate the force on columns based on shape, and size for a range of blast intensities. Also, it is attempted to approximate the response of columns with an equivalent single-degree of freedom (SDOF) model. The parameters of the equivalent single-degree of freedom are calibrated via simulation results. Due to the relatively short duration of blast loading in comparison with columns\u27 natural period, column responses are mainly impulse-sensitive. The proposed equations in conjunction with SDOF model can be beneficial tools in blast design practices. Furthermore, the damage and failure modes of columns are studied. For columns that prove insufficient, the efficacy of retrofitting measures such as steel jackets have been investigated

Evaluation of FEM modelling for stress propagation under pressure wheel of corn planter

Seeds need a certain range of pressure in the soil bed to germinate and grow ideally. Usually pressure from machinery wheels applies more pressure and prevents seed ideal germination. A finite element model (FEM) was developed to investigate stress propagation in the soil. The pressure wheel of corn planter with 4 km/h speed was chosen to analyze the stress in a sandy-loamy soil. A real corn planter tire was modeled with its mechanical characteristics and imported into ABAQUS/Explicit environment. Frictional contact (based on Mohr-coulomb theory) was used for the soil-tire interaction. The soil was considered as an elastic-perfectly plastic material. Drucker-Prager model was used for soil behavior in plastic region. To evaluate the stress under pressure wheel, FEM results were compared with the Boussinesq theoretical model. On both models, soil stresses decrease with soil depth increasing from zero depth on soil surface to 0.2 m depth. On FEM, stress distribution varied between 47.8 to 8.1 kPa in depth of 0.01 to 0.2 m. FEM and Boussinesq models showed high correlation with each other (R2=95). Our results indicate that the stress under pressure wheels can be properly predicted by using FEM, allowing the pressure simulation to reduce the negative impacts on seed germination and crop yield

Evanescent wave optical trapping and sensing on polymer optical fibers for ultra-trace detection of glucose

Graphene sensitization of glucose-imprinted polymer (G-IP)-coated optical fiber has been introduced as a new biosensor for evanescent wave trapping on the polymer optical fiber to detect low-level glucose. The developed sensor operates based on the evanescent wave modulation principle. Full characterization via atomic force microscopy (AFM), Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), Raman spectroscopy, high-resolution transmission electron microscopy (HRTEM), and N2 adsorption/desorption of as-prepared G-IP-coated optical fibers was experimentally tested. Accordingly, related operational parameters such as roughness and diameter were optimized. Incorporating graphene into the G-IP not only steadily promotes the electron transport between the fiber surface and as-proposed G-IP but also significantly enhances the sensitivity by acting as a carrier for immobilizing G-IP with specific imprinted cavities. The sensor demonstrates a fast response time (5 s) and high sensitivity, selectivity, and stability, which cause a wide linear range (10–100 nM) and a low limit of detection (LOD = 2.54 nM). Experimental results indicate that the developed sensor facilitates online monitoring and remote sensing of glucose in biological liquids and food samples

Dynamic Characteristics of Bubbling and Turbulent Fluidization Using Hurst Analysis Technique

A non-intrusive vibration monitoring technique was used to study the flow behavior in a fluidized bed. This technique has several advantages compared to other techniques, such as pressure probes and optical fiber probes which may influence the measurement because they are intrusive. Experiments were conducted in a 15 cm diameter by 2 m tall fluidized bed using 470 micron sand particles. Auto correlation functions, mutual information function and Hurst exponent analyses were used to analyze the fluidized bed hydrodynamics near the transition point from bubbling to turbulent fluidization regime. These methods were able to detect the regime transition point using vibration signals

A New Approach for Modeling of a Fluidized Bed by CFD-DEM

Numerical studies of 3D cylindrical fluidized bed by means of combined computational fluid dynamics (CFD) and discrete element method (DEM) were carried out. For motion of particles, Newton\u27s second law and 3D compressible Navier-Stokes equations in generalized curvilinear coordinates in its conservative form were used. Navier-Stokes equations were solved with high order compact finite difference scheme by fully implicit flux decomposition method. Non-reflecting boundary conditions (NRBC) were used for the outflow boundary. The convergence of this method, especially at high Reynolds number, is significantly better than the SIMPLE method

Optimal route planning of agricultural field operations using ant colony optimization

Farming operations efficiency is a crucial factor that determines the overall operational cost in agricultural production systems.  Improved efficiency can be achieved by implementing advanced planning methods for the execution of field operations dealing, especially with the routing and area coverage optimisation aspects. Recently, a new type of field area coverage patterns, the B-patterns, has been introduced.  B-patterns are the result of a combinatorial optimisation process that minimizes operational criterions such as, the operational time, non-working travelled distance, fuel consumption etc.  In this paper an algorithmic approach for the generation of B-patterns based on ant colony optimisation is presented.  Ant colony optimization metaheuristic was chosen for the solution of the graph optimisation problem inherent in the generation of B-patterns.  Experimental results on two selected fields were presented for the demonstration of the effectiveness of the proposed approach. Based on the results, it was shown that it is feasible to use ant colony optimization for the generation of optimal routes for field area coverage while tests made on the resulting routes indicated that they can be followed by any farm machine equipped with auto-steering and navigation systems