Characterizing the influence of reinforcing resin on the structure and the mechanical response of filled isoprene rubber

In the present study, a specific type of reinforcing resin behavior is investigated using various mechanical approaches as well as microscopic techniques such as transmission electron microscopy and atomic force microscopy. Based on these observations, it could be concluded that the reinforcing resin introduces a synergistic effect with carbon black in order to strengthen the system. This is implied since the percolation threshold is significantly reduced and the morphology of the filler aggregates changes toward higher compactness, i.e., an increase of volume-to-size ratio with the addition of resin.     

Birefringence via Doppler broadening and prevention of information hacking

We propose a new scheme for the coherent control of birefringent light pulses propagation in a four-level atomic medium. We modify the splitting of a light pulse by controlling the electric and magnetic responses. The Doppler broadening effect is also noted on the propagation of the birefringent pulses. The dispersions of the birefringence beams are oppositely manipulated for delay and advancement of time at a Doppler width of 10γ. A time gap is created between the birefringence beams, which protects from hacking of information. The time gap is then closed to restore the pulse into the original form by a reverse manipulation of the dispersion of the birefringence beams, i.e., introducing another medium whose transfer function is the complex conjugate of that of the original medium. The results are useful for secure communication technology.     

Ultra-broadband piezoelectric energy harvesting via bistable multi-hardening and multi-softening

Nonlinear Dynamics - An electromechanical coupled distributed parameter model is derived for a broadband piezoelectric energy harvester with nonlinear magnetic interaction and...     

Nonlinear closure modeling in reduced order models for turbulent flows: a dynamical system approach

Nonlinear Dynamics - Reduced-order models (ROM) of structurally dominated fluid flows have significant applications in science and engineering, such as design, control, and optimization....     

F(1H-Pyrazol-4-yl)methylene-Hydrazide derivatives: Synthesis and antimicrobial activity

This paper investigates the seismic and collapse performance of shape memory alloy (SMA) braced steel frame structures considering the effects of various brace design parameters and ultimate state of SMAs. An SMA braced steel frame building is designed to have comparable strength and stiffness with a steel-moment resisting frame selected as case study building. Then, the stiffness and ultimate deformation capacity of the SMA braces in the initially designed reference SMA braced frame are systematically varied. First, the static pushover analysis and incremental dynamic analysis (IDA) are employed to illustrate the significance of SMA brace failure consideration in seismic performance assessment of steel frames with SMA elements. Then, the influence of SMA brace initial stiffness and ultimate deformation capacity on the seismic and collapse performance of SMA braced frames are studied through pushover analyses, nonlinear response history analyses, and IDA. The results show that the SMA brace initial stiffness does not affect the interstory drift and floor absolute acceleration response at design and maximum considered earthquake (MCE) level seismic hazard or collapse capacity of the frame. However, it has considerable influence on post-event functionality of the frame. It is also found that the SMA brace ultimate deformation capacity should be at least 80% of maximum inter-story drift demand at MCE level for satisfactory seismic performance, while larger values provide higher collapse capacity for the SMA braced frame.     

Solvent Effects in the Homogeneous Catalytic Reduction of Propionaldehyde with Aluminium Isopropoxide Catalyst: New Insights from PFG NMR and NMR Relaxation Studies

Solvent effects in homogeneous catalysis are known to affect catalytic activity. Whilst these effects are often described using qualitative features, such as Kamlet-Taft parameters, experimental tools able to quantify and reveal in more depth such effects have remained unexplored. In this work, PFG NMR diffusion and T₁ relaxation measurements have been carried out to probe solvent effects in the homogeneous catalytic reduction of propionaldehyde to 1-propanol in the presence of aluminium isopropoxide catalyst. Using data on diffusion coefficients it was possible to estimate trends in aggregation of different solvents. The results show that solvents with a high hydrogen-bond accepting ability, such as ethers, tend to form larger aggregates, which slow down the molecular dynamics of aldehyde molecules, as also suggested by T₁ measurements, and preventing their access to the catalytic sites, which results in the observed decrease of catalytic activity. Conversely, weakly interacting solvents, such as alkanes, do not lead to the formation of such aggregates, hence allowing easy access of the aldehyde molecules to the catalytic sites, resulting in higher catalytic activity. The work reported here is a clear example on how combining traditional catalyst screening in homogeneous catalysis with NMR diffusion and relaxation time measurements can lead to new physico-chemical insights into such systems by providing data able to quantify aggregation phenomena and molecular dynamics.     

Rapid Learning-Based and Geologically Consistent History Matching

Various types of data become available at different stages of a reservoir’s life. The production data are integrated into the flow simulation models through a process referred to as history matching. The history-matching process is iterative, and it usually involves a large number of simulation runs. Hence, this process requires significant computational time. In most history-matching methods, the initial geological assumptions in the reservoir model are destroyed or significantly altered in the process. Furthermore, they do not account for the information obtained during the previous trials, and lack learning from the previous failures. In this paper, we introduce a new methodology that maintains the geological realism. The candidate realizations are selected through a learning-based history-matching (LHM) algorithm by which all the previously successful patterns are preserved and used to assist the construction of the next realizations. The various pieces of matching regions are assembled together to make a pool of the successful candidates. Such regions are then utilized for making an auxiliary dataset in a multiscale framework by which the next model is generated. To prevent from trapping in local minima, ideas from the genetic algorithm is adapted. The LHM algorithm can be applied to both categorical and continuous distributions. The LHM provides a conditional map by which the new production data are immediately incorporated into the existing reservoir models. We apply the LHM algorithm to various 2D and 3D examples with very complex binary and continuous properties. The algorithm is shown to produce history-matched models with significantly smaller CPU times.     

Numerical simulation of unsteady 3D magneto-Sisko fluid flow with nonlinear thermal radiation and homogeneous–heterogeneous chemical reactions

In this paper, we study the qualitative behaviour of satellite systems using bifurcation diagrams, Poincaré section, Lyapunov exponents, dissipation, equilibrium points, Kaplan–Yorke dimension etc. Bifurcation diagrams with respect to the known parameters of satellite systems are analysed. Poincaré sections with different sowing axes of the satellite are drawn. Eigenvalues of Jacobian matrices for the satellite system at different equilibrium points are calculated to justify the unstable regions. Lyapunov exponents are estimated. From these studies, chaos in satellite system has been established. Solution of equations of motion of the satellite system are drawn in the form of three-dimensional, two-dimensional and time series phase portraits. Phase portraits and time series display the chaotic nature of the considered system.