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Understanding the droplet size distribution of subsea oil releasing is important to predict the subsequent transport and degradation of the spilled oil. Single- and multi-phase oil jet experiments were conducted in the Ohmsett facility, including pure oil jet and oil-air jet through a 10.7-mm pipe and a 4.7-mm pipe. Measurements of the vertical jet hydrodynamics and the oil size distribution were obtained. The reported results help to extend subsea oil spills experiment scale into a meso-scale, and the measurement range of the oil size is widened up to 2 cm. Moreover, the application of dispersant and involvement of air phase provided valuable scientific evidence for the usage of dispersants to treat oil spills. The data confirmed the effectiveness of the dispersant that reduces oil droplet size and also suggested that the participation of the gas phase facilitated the decreasing of oil droplet size. The results were compared to the numerical simulation tool VDROP-J. While the hydrodynamics showed good consistency, the system-dependent coefficient needed a slight revision to coincide with presented data. This also confirmed the significance of experimental materials for further validation and development of oil spill models, where we also provided guidance and discussion on conducting and post-processing the oil spill experiment.

Oil dispersion under a deep-water plunging breaker of height 0.15 m was studied by coupling the Lagrangian particle tracking code (NEMO3D) with the population balance model (VDROP). The wave hydrodynamics obtained in Part I (Cui et al. in Environ Fluid Mech 2020 (in press)) was used as input. It was observed that droplet inertia and major forces on droplets significantly impacted the transport of oil droplets under wave conditions, and neglecting it caused less entrainment into the water column and horizontal spread of oil plume. For droplets less than 400 microns, the droplet size distribution (DSD) tended to follow a power-law distribution with an exponent close to − 2.3, which was consistent with earlier experimental observations by Delvigne and Sweeney (Oil Chem Pollut 4(4):281–310, 1988). The distribution of large size droplets evolved with time and showed agreement with a power-law distribution having an exponent of − 9.7 about 20 s after the passage of the wave train. Reducing the interfacial tension enhanced droplets breakup and increased the exponent of power-law distribution to − 6.1 for droplets smaller than 400 microns. It was also found that neglecting the vertical gradient of eddy diffusivity led to the accumulation of oil droplets in low eddy diffusivity regions at the bottom part of the wave breaker. The investigation herein could be used to obtain design values for breakers that could be used in oil spill models to predict the oil droplet size distribution.

The dispersion (transport and breakup) of oil droplets under breaking waves is essential for evaluating the impact of oil spills on the environment, and for designing countermeasures. In this part of the work (Part I), the hydrodynamics of a wave breaker in a 1.0 m deep tank obtained experimentally by Rapp and Melville (Philos Trans R Soc Lond A Math Phys Eng Sci 331(1622):735–800, 1990) using the dispersive focusing method was investigated numerically using Reynold-averaged Navier–Stokes (RANS) within the CFD code ANSYS Fluent. The renormalization group (RNG) k–e turbulence closure model was adopted to simulate wave turbulence, and the transient water–air interface was captured using volume of fluid (VOF) method. The simulated surface excursion and velocity fields matched closely the experimental observations during wave breaking. The energy dissipation of the wave crest showed good agreement with recent laboratory work and numerical simulations through evaluating the breaking parameter. The RANS approach was able to reproduce the turbulent kinetic energy field engendered by the breakers and simulated the residual turbulence within about two wave periods after the passage of the wave train. The VOF scheme Compressive provided a better agreement with the observation than the Geo-reconstruct scheme. The approach herein suggests that RANS method coupled with VOF in ANSYS Fluent is capable of capturing the major hydrodynamic forces and turbulence, and thus could be used to predict environmental processes within the breaking waves such as oil droplet formation and transport.

Response surface methodology is used in this study to model and optimize a solar thermal-photovoltaic vacuum membrane distillation (STPVMD) system with PVDF hollow fiber membrane. Regression models have been developed to forecast the effect of various operation factors on the permeate flux and the energy consumption. The operation factors in the model include the feed inlet temperature, the feed flow rate and the vacuum pressure. Analysis of variance is used to statistically validate the regression models. With permeate flux as the objective function of optimization, the optimal operation parameters are found to be 63 °C for the feed inlet temperature, 237 L / h for the feed flow rate, and 750 kPa for the vacuum pressure. Experimental tests show that the resulting permeate flux is 6.26 L / m 2 · h , which is slightly higher than the predicted value of 6.05 L / m 2 · h . The corresponding energy consumption is predicted to be 12.52 L / kW · h , demonstrating the effectiveness and reliability of the models.

Understanding the size of oil droplets released from a jet in crossflow is crucial for estimating the trajectory of hydrocarbons and the rates of oil biodegradation/dissolution in the water column. We present experimental results of an oil jet with a jet-to-crossflow velocity ratio of 9.3. The oil was released from a vertical pipe 25 mm in diameter with a Reynolds number of 25 000. We measured the size of oil droplets near the top and bottom boundaries of the plume using shadowgraph cameras and we also filmed the whole plume. In parallel, we developed a multifluid large eddy simulation model to simulate the plume and coupled it with our VDROP population balance model to compute the local droplet size. We accounted for the slip velocity of oil droplets in the momentum equation and in the volume fraction equation of oil through the local, mass-weighted average droplet rise velocity. The top and bottom boundaries of the plume were captured well in the simulation. Larger droplets shaped the upper boundary of the plume, and the mean droplet size increased with elevation across the plume, most likely due to the individual rise velocity of droplets. At the same elevation across the plume, the droplet size was smaller at the centre axis as compared with the side boundaries of the plume due to the formation of the counter-rotating vortex pair, which induced upward velocity at the centre axis and downward velocity near the sides of the plume.

During undersea oil blowout in crossflow conditions, the oil droplets entrained horizontally which increased the residence time of droplets in the water column. Knowledge of the trajectory of an oil plume is important for predicting the pathways of hydrocarbons and to devise countermeasures. We conducted large-scale experiments in the Ohmsett tank where we released oil from a one-inch vertical orifice that was towed to produce the behavior of a jet in crossflow. The average oil velocity at the orifice was 1.36 m/s and the crossflow velocity was around 0.27 m/s which resulted in a jet-to-crossflow velocity ratio of 5.0. The results were simulated numerically using the Large Eddy Simulation (LES) turbulence model and the mixture multiphase model within the open-source software OpenFOAM. The instruments including ADVs, LISSTs, shadowgraph cameras, holographic camera, and fluorometers were employed. The oil jet released from the nozzle started to meander in the vertical direction most probably due to weak crossflow. The trajectory and meandering behavior of the oil jet, wavy pattern along the leading edge of the jet and column breakup observed in the experiments were captured well with the numerical simulation. The surface breakup just above the orifice created ligaments and droplets downstream of the jet. Larger oil droplets were observed near the upper boundary of the plume due to their higher buoyancy while the smaller droplets were suspended in the water column and they were entrained by water crossflow. This work reveals that different size of droplets determines the overall shape of plumes mostly the upper and lower boundaries of the plume.

(1141370) Wave tank experiments were performed to measure the droplets size distribution under the plunging breaking wave. A deep-water plunging breaker of height 20 cm was generated using the dispersive focusing method, and a shadowgraph camera was used to take images of droplets and bubbles of different sizes. For droplets smaller than the 1000 microns, the number-based DSD matched the DS correlation (Delvigne and Sweeney 1988), which gives N(d) ~ d−2.3, but N(d) ~ d−9.7 for diameters larger than 1000 microns. A numerical method was designed to study the oil dispersion under breaking waves by coupling the computational fluid dynamic (CFD) with the Lagrangian particle tracking code (NEMO3D) and population balance model (VDROP). The wave hydrodynamics was reproduced using the Reynolds-averaged Navier Stokes approach within a commercial CFD code ANSYS Fluent. The obtained wave hydrodynamics was then used as inputs for the NEM3D code and VDROP model. The numerical results show reasonable agreement with our experimental observation. The approach adopted to produce the DSD reduces the empiricism of the DS correlation, as the approach uses oil properties and measurable wave properties. The proposed numerical method was ready to be used in other scenarios of oil spills (i.e., oil jets in deep oceans and oil dispersion in riverine systems). It could also be potentially used in large scale forecast and hindcast simulations for oil spill response and research.

A numerical framework was developed to study oil-particle aggregate (OPA) formation by incorporating NEMO3D code and the A-DROP model into an open-source platform, OpenFOAM. The developed f...

The transport of virus-laden particles was investigated numerically in an archetypical supermarket configuration of area 1,200 m2 and ceiling height of 4.5 m. The particles were tracked u...

Theoretical arguments and numerical investigations were conducted to understand the transport of oil droplets under ice. It was found that the boundary layer (BL) in the water under ice produces a downward velocity that reaches up to 0.2% of horizontal current speed, and is, in general, larger than the rise velocity of 70 μm oil droplets. The eddy diffusivity was found to increase with depth and to decrease gradually afterward. Neglecting the gradient of eddy diffusivity when conducting Lagrangian transport of oil droplets would result in an unphysical spatial distribution. When the downward velocity of water was neglected, oil accumulated at the water-ice interface regardless of the attachment efficiency. The lift force was found to scrape off droplets of the ice, especially for droplets ≤ 70 μm. These findings suggest that previous oil spill simulations may have overestimated the number of small droplets (≤70 μm) at the water-ice interface.

The dispersion of oil droplets in rivers was numerically investigated for uniform flow in a hypothetical wide river with a depth of 3.0 m. The river hydrodynamics profile was used in conju...

Knowledge of the droplet size distribution (DSD) of spilled oil is essential for the accurate prediction of oil transport, dissolution, and biodegradation. Breaking waves play important roles in oil droplet formation in oceanic environments. To understand the effects of breaking waves on oil DSD, oil spill experiments were designed and performed in a large-scale wave tank. A plunging breaker with a height of about 0.4 m was produced using the dispersive focusing method within the tank. Oil placed within the breaker resulted in a DSD that was measured using a shadowgraph camera and found to fit a Gaussian distribution (&micro, = 1.2 mm, &sigma, 2 = 0.29 mm2). For droplets smaller than 1500 &micro, m, the number-based DSD matched the DS1988 correlation [1], which gives N(d) ~ d-2.3, but this was N(d) ~ d-9.7 for droplets larger than 1500 &micro, m. An order of magnitude investigation revealed that a Gaussian volume-based DSD results in a number-based DSD that may be approximated by d-b (with b &asymp, 2) for small diameters (relative to the mean), which explains the occurrence of the DS1988 correlation. With the measured wave hydrodynamics, the VDROP model was adopted to simulate the DSD, which closely matched the observed DSD. The present results reduce the empiricism of the DS1988 correlation.

With the increase in transport of oil by rail, the probability of oil spills in rivers has increased. Traditionally, focus has been placed on oil slicks moving on the water surface. However...

Langmuir supercells (LS) are full-depth Langmuir circulations in unstratified shallow shelves. A Reynolds-averaged Eulerian formulation is developed resolving LS as a secondary component to the wind-driven mean shear current. This formulation is combined with Lagrangian particle tracking to investigate oil droplet entrainment induced by LS as a function of wind stress. Two cases are simulated, one in which 500-μm oil droplets are released into a steady field of LS generated by a wind stress of 0.1 N m−2 and waves of intermediate wavelength λ = 6 H where H = 15 m is the water column depth, significant amplitude of 0.6 m and period of 8 s. In the second case, the 500-μm oil droplets are released into a steady field of LS generated by the same wave forcing but with a weaker wind stress of 0.025 N m−2. It is found that the greater wind stress leads to LS able to spread the droplets throughout upwelling and downwelling limbs of the cells within the first 80 minutes after release. The weaker wind leads to weaker LS that, within the same time after release, limit the dispersion of the droplets to the downwelling limbs of the cells forming Stommel retention zones for a prolonged time.

Understanding the shear breakup in jet flows and the formation of droplets from ligaments is important to determine the final droplet size distribution (DSD). The initial droplet size, which affects the final DSD, is considered to be generated by the shear breakup. Large eddy simulation (LES) was performed to investigate the shear breakup in liquid-liquid jet flows. The explicit Volume of Fluid (VOF) model with the geometric reconstruction scheme was used to capture the oil-water interface. The estimated oil distribution including wave peaks, ligaments, droplets and water streaks were compared to the experiments with a good agreement. The estimated DSD matched with the measurements favorably well. In the simulation, the formation of droplets with a smooth and curved surface from ligaments or sheet-like structures was obtained. Different mechanisms were observed along with the shear layer including the formation of droplets from ligament through the capillary forces, breakage of a droplet into smaller ones and attachment of a droplet to a ligament. The destructive shear forces and resisting surface tension forces were quantified on stretching and retracting ligaments. The influence of internal viscous force was found to be negligible due to low oil viscosity. The critical capillary number was found to be larger than 5.0 for ligaments breaking with the shear breakup. The capillary number was below unity for retracting ligaments. The coalescence of two equal-sized droplets was obtained in the shear breakup region. The shear stress magnitude at the contact region increased more than two folds. The total surface area decreased nearly 20% after the coalescence.

A numerical study was undertaken to investigate subsurface release and fate of benzene and toluene in a tidally influenced beach. The simulations were conducted by using a numerical model BIOMARUN, which coupled a multi-Monod kinetic model BIOB to a density-dependent variably saturated groundwater flow model MARUN. The fate and transport of the contaminant plume were characterized by computing its centroid trajectory, spreading area and percentage of biodegradation in beach saturated and unsaturated zone, respectively. Key factors likely affecting this process were investigated, including tide amplitude, capillarity and hydraulic conductivity. It was found that aerobic biodegradation was the major fate of the contaminant plume in the beach. Tidal action twisted the centroid of the contaminant plume during its migration in the beach, which increased the residence time of the plume in the beach. High tidal range significantly altered the spatial distribution of the contaminant biodegradation in the beach. In contrast, the capillary fringe had impacts on the percentage of benzene biodegraded in the saturated and unsaturated zone of the beach. The increase in capillary fringe enhanced the percentage of the contaminant biodegraded in the unsaturated zone, up to 40%, which is comparable to that in the saturated zone. Hydraulic conductivity seemed to have large impacts on the biodegradation rate of the contaminant in the beach. Higher hydraulic conductivity induced faster contaminant biodegradation in the beach.

Shape memory polymers (SMPs) are soft active materials that have an ability to retain a temporary shape, and revert back to their original shape when triggered by a suitable stimulus, typically an increase in temperature. These materials are finding wide use in a variety of fields such as biomedical and aerospace engineering; hence it is important to model their mechanical behavior. Crystallizable shape memory polymers (CSMPs) is an important subclass of SMPs, and their temporary shape is fixed by a crystalline phase, while return to the original shape is due to the melting of this crystalline phase. In our earlier work, we have studied the mechanical behavior of CSMPs within a mechanical setting by considering the original amorphous network above the recovery temperature as a hyperelastic material. In this article, we extend our earlier work to incorporate the temperature-dependent viscoelasticity into the developed constitutive model to study the mechanical behavior of CSMPs. The viscoelastic behavior of the polymers at high temperature is simulated through a rate type model. Furthermore, the model of the semi-crystalline polymer after the onset of crystallization is developed based on the mixture theory and the theory of “multiple natural configurations”. In addition, we have applied the model to a specific boundary value problem, namely uniaxial extension. The shape memory cycles of the CSMPs under different stretch rates have been studied. The results are consistent with what has been observed in experiments.

Summary Shape-memory polymers (SMPs) belong to a class of smart materials that have shown promise for a wide range of applications. They are characterized by their ability to maintain a temporary deformed shape and return to an original parent permanent shape. In this paper, we consider the coupled photomechanical behavior of light activated shape-memory polymers (LASMPs), focusing on the numerical aspects for finite element simulations at the engineering scale. The photomechanical continuum framework is summarized, and some specific constitutive equations for LASMPs are described. Numerical implementation of the multiphysics governing partial differential equations takes the form of a user defined element subroutine within the commercial software package ABAQUS. We verify our two-dimensional and three-dimensional finite element procedure for multiple analytically tractable cases. To show the robustness of the numerical implementation, simulations are performed under various geometries and complex photomechanical loading. Copyright © 2016 John Wiley & Sons, Ltd.

Understanding the trajectory of oil droplets in crossflow jets is important to estimate the pathways of hydrocarbons and to plan countermeasures. We report experimental results of an oil jet with release velocity around 1.5 m/s in a crossflow of 0.3 m/s. The hydrodynamics of the jet obtained with the Large Eddy Simulation (LES) were used to predict the migration of the oil droplets. Two Lagrangian techniques were explored, one with the inertia of the droplet is considered and the other that treats the droplets as massless particles with rising velocities corresponding to their size. We did not note a large difference between the two approaches. The droplets showed stronger segregation in the vertical direction, which renders the usage of a Gaussian distribution approximation in the vertical inapplicable. The dispersion coefficient at each direction was computed for different-sized droplets. The eddy diffusivity computed based on Boussinesq gradient approximation using the LES data was compared with the dispersion coefficients obtained based on Lagrangian tracking. We also found that droplets 500 μ m and larger escape the vortex while smaller ones get trapped within the vortex. A similar outcome was observed using a vortex trapping function based on inward–outward force balancing at the elevation of the vortex core. The counter-rotating vortex pair (CVP) altered the distribution of droplets of 1 mm and smaller significantly, and bimodal concentration distributions with peaks near the CVP vortex cores and minimum concentration near the center plane were obtained in the lateral–horizontal​ direction. Therefore, measurements of the oil droplet size distribution (DSD) in the center plane of crossflow jets could underestimate the number of small droplets in the whole plume.

Experimental results were presented for the release of diesel oil from a one-inch (2.5 cm) vertical pipe in a crossflow at 0.27 m/s. The ratio of jet velocity to crossflow speed was 5.0 and the Reynolds number based on jet velocity and pipe diameter was 7.1 × 10 3 . In the experiments, the plume shape was photographed, and the oil droplets were measured at two vertical locations on the center axis of the plume. Acoustic Doppler velocimetry (ADV) data was also obtained and compared to numerical predictions. The plume was simulated using large eddy simulation (LES), and the mixture multiphase model. The impact of the oil buoyancy was captured by adding a transport term to the volume fraction equation. Using the rise velocity based on d50 (volume-median) droplet size in the lower part of the plume allowed us to capture the lower boundary of the plume, but the estimated upper boundary of the plume penetrated less into the crossflow as compared to the experimental findings. However, using the rise velocity of the d50 at the upper part of the plume allowed one to estimate the upper boundary of the plume. As the droplets are too small to be resolved by the LES, we could not use a systematic approach to allow the multiphase plume to spread to mimic the observations. Based on the simulation results, the interaction between the jet and crossflow yielded small-sized flow structures near the upper boundary of the plume. The wake vortices initiated from the leeward side of the plume showed an alternating vorticity pattern in the wake. The shear layer vortices were induced by Kevin-Helmholtz instabilities mostly on the windward side of the plume. The formation of counter rotating vortex pair (CVP) altered greatly the hydrodynamics of the jet from that of a vertical jet to manifest flow reversals in all directions. The formation of CVP is likely to enhance the mixing of chemicals and droplets within the plume.

Shape memory polymers (SMPs) are smart materials that alter their shape in response to external stimuli. Dual-shape SMPs are widely recognized and are characterized by two shapes involved in a typical shape memory cycle. Recently, triple-shape memory polymers (TSMPs) have been introduced that have the ability to remember three shapes. Thermo-sensitive TSMPs can perform two sequential shape changes in response to heat, which were programed previously in a triple-shape creation process (TSCP). TSMPs are technologically significant as their development of has led to emergence of many complex potential applications that cannot be achieved by dual-shape polymers (Zhao et al., 2013). Crystallizable TSMPs are a class of thermo-sensitive TSMPs, where the shape creation is due to formation of crystalline phases. Different TSCPs have been reported which enable to control the triple shape capability of these materials. In this work the mechanical behavior of TSMPs has been modeled using a framework that has been developed recently for studying crystallization in polymers (Rao, 2003; Rao and Rajagopal, 2001, 2002, 2004). The framework has been used successfully to model SMPs (Barot and Rao, 2006; Barot et al., 2008), light activated SMPs (Sodhi and Rao, 2010) and is based upon the theory of multiple natural configurations. The model has been used to simulate a uni-axial deformation cycle for different types of TSCPs and the results have been compared with experimental data.

Canada's production, transport, and sale of diluted bitumen (dilbit) products are expected to increase by a million barrels per day over the next decade. The anticipated growth in oil production and transport increases the risk of oil spills in aquatic areas and places greater demands on oil spill capabilities to respond to spills, which have raised stakeholder concerns. Current oil spill models only predict the transport of bitumen blends that are used in contingency plans and oil spill response strategies, rather than changes in the oil's physical properties that are relevant to spill response. We conducted weathering studies of five oil products (two conventional oils and three bitumen blends) in the Department of Fisheries and Oceans' flume tank. We also considered two initial oil slick thicknesses, 4.0 mm and 7.0 mm. We found that there is a major difference in the time evolution of oil properties (density and viscosity), raising doubts on weathering models that do not consider the thickness of oil. We also developed empirical expressions for the evolution of the density and viscosity of these oil products. The findings from the 4.0 mm results were incorporated with data from the literature to provide an update on the factors to consider during the decision making for spills of diluted bitumen products. The matrix indicated that most response options, including chemical dispersants, work much more effectively within 48 hours of the initiation of weathering. After this window of opportunity closes, natural attenuation or in situ burning is the only option remaining, but containment of oil is a limiting factor for in situ burning.

The capacity of a material to sense its environment and to change its shape on demand in a predefined way has tremendous technological significance for a wide variety of application areas. Shape memory polymers (SMPs) belong to this category of smart materials as they have the ability to undergo a shape change in a predetermined manner under the influence of an external stimulus. SMPs can recover their permanent shape after undergoing large deformation to a temporary shape on exposure to external triggers such as light, PH values and heat. Thermally induced SMPs are first generation SMPs and have been widely recognized. Crystallizable SMPs are a class of thermally induced SMPs whose temporary shape is due to formation of crystalline phases, and they will revert back to their permanent shape when the crystallization phase is melted through heating. Traditional crystallizable SMPs can only perform dual-shape memory cycles and this limits applications of crystallizable SMPs. Recently SMPs with triple shape effect have been reported that can switch from a second temporary shape to the first temporary shape and from there to the permanent shape under stimulation by heat. Our research focuses on modeling the mechanical behavior of these SMPs with triple-shape effect. The framework used in developing the model is built upon the theory of multiple natural configurations [3]. In order to model the mechanics associated with these polymers different stages of the shape fixation and recovery cycle and different phases of the material during this cycle need to be characterized. This includes developing a model for the amorphous phase and the subsequent semi-crystalline phases with different stress free states and melting of these phases. The model subsequently has been used to simulate results for a typical deformation cycle involving circular shear.Copyright © 2015 by ASME

Shape Memory polymers (SMPs) is a novel class of smart polymeric materials that have been attracted tremendous scientific interest within the last decades. SMPs have the ability to “remember” their original shape even after undergoing significant deformation into a temporary shape. For most first generation of SMPs, the shape memory effect was accomplished by a thermally induced process, triggered in many different ways, such as heating/cooling, electromagnetic field and infrared light. The transient shape in thermally induced SMPs is due to a glassy phase or a semi-crystalline phase. The thermally induced SMPs which temporary shape is fixed through crystallization is called crystallizable shape memory polymers (CSMPs). For traditional CSMPs, their original shape is predefined and is not able to be reprogrammed. This limits the applications of the CSMPs. Recently, a new class of CSMPs has been developed. These materials can perform a typical thermally induced shape memory cycle, but their original shape can be reprogrammed through exposing to UV light. The shape reprogramming effect is governed by light induced covalent bonds exchange reaction, while the shape memory effect-as typical CSMPs-is due to solid-phase crystallization. In this work, we focus on modeling the mechanical behavior of this new class of structurally dynamic CSMPs. The framework used in developing the model is built upon the theory of multiple natural configurations[1]. The model has been applied to solve a specific boundary condition problem, namely uni-axial tension. Furthermore, we implement our model through Abaqus (commercial finite element package) subroutine UMAT to simulate 3D behavior of this attractive material.Copyright © 2015 by ASME

Shape memory polymers (SMP’s) are polymers that have the ability to retain a temporary shape, which can revert back to the original shape on exposure to specific triggers such as increase in temperature or exposure to light at specific wavelengths. A new type of shape memory polymer, light activated shape memory polymers (LASMP’s) have been developed in the past few years. In these polymers the temporary shapes are fixed by exposure to light at a specific wavelength. Exposure to light at this wavelength causes the photosensitive molecules, which are grafted on to the polymer chains, to form covalent bonds. These covalent bonds are responsible for the temporary shape and act as crosslinks. On exposure to light at a different wavelength these bonds are cleaved and the material can revert back to its original shape. A constitutive model of LASMP’s which based on the notion of multiple natural configurations has been developed (see Sodhi and Rao [1]). It has been applied to model the circular shear of light activated shape memory polymer with two networks. In this work we use this model to analyze the mechanical behavior of LASMP’s with three different networks undergoing a circular shear deformation cycle. This involves study of the behavior of the LASMP’s when two temporary configurations are formed by exposing the polymer to light at different time during the deformation process. In addition, we show that these materials are able to undergo complex cycles of deformation due to the flexibility with which these temporary configurations can be formed and removed by exposure to light.Copyright © 2013 by ASME

Shape memory polymers (SMP’s) are polymers that have the ability to retain a temporary shape, which can revert back to the original shape on exposure to specific triggers such as increase in temperature or exposure to light at specific wavelengths. A new type of shape memory polymer, light activated shape memory polymers (LASMP’s) have been developed in the past few years. In these polymers the temporary shapes are fixed by exposure to light at a specific wavelength. Exposure to light at this wavelength causes the photosensitive molecules, which are grafted on to the polymer chains, to form covalent bonds. These covalent bonds are responsible for the temporary shape and act as crosslinks. On exposure to light at a different wavelength these bonds are cleaved and the material can revert back to its original shape. A constitutive model of LASMP’s which based on the notion of multiple natural configurations has been developed (see Sodhi and Rao[1]). In this work we use this model to analyze the mechanical behavior of LASMP’s under a specific boundary value problem, namely, the problem of circular shear. We use this model problem to study the behavior of the LASMP’s when a temporary configuration is formed by exposing the polymer to light. In addition we show that these materials are able to undergo complex cycles of deformation due to the flexibility with which these temporary configurations can be formed and removed by exposure to light.

Shape memory polymers (SMPs) are soft active materials, their special property is the ability to hold a temporary shape and when exposed to a suitable trigger, they come back to their original shape. These external stimuli can be temperature, light or electro-magnetic fields. Amorphous SMPs are a class of thermally-activated SMPs that rely on glass transition to retain their temporary shape. Above the glass transition temperature (T > Tg), (amorphous SMPs exhibit finite deformation and viscoelastic behavior. In this work we develop a model to capture the viscoelastic behavior of the amorphous SMPs at elevated temperatures. The model uses an approach that was initially developed to study non-Newtonian viscoelastic fluids. We accomplish this by developing a multi-branch model based on the theory of multiple natural configurations using the maximization of the rate dissipation to determine the evolution of the natural configurations. We apply our model to study several different deformations at an elevated temperature T = 130 °C and show that this approach is able to capture the viscoelastic behavior of these polymers. The predictions of the theory are then compared with experimental results.

Bayesian network is a graphics mode which is used to show joint probability distribution. It reflects the potential dependence relationship among variables. The Bayesian network has already been the powerful tool to solve various uncertain questions. This thesis collects some information about traffic accidents in a city of Anhui Province. According to the information, it gets the Markov network firstly. Secondly, it gives directions to all edges of the Markov network according to the mutual degree of dependence. Finally, it reaches the Bayesian network which shows the relationship of uncertain factors in traffic accidents.