Linear and nonlinear viscoelastic and viscoplastic analysis of asphalt binders with warm mix asphalt additives

Warm-Mix Asphalt (WMA) is a widely used product, which proved a contribution to the reduction in asphalt mixing and compaction temperatures. This reduction leads to lower fuel consumption and smoke emission in asphalt plants. Most of the characterisation of binders used in WMA has focused in the past on measuring linear viscoelastic properties and associated Superpave parameters. Several studies have shown that the average stresses and strains of the asphalt mixture remain mostly within the linear viscoelastic response. However, localised strains in the binder phase of the mixture could reach values high enough to induce nonlinear viscoelastic and viscoplastic deformations. Therefore, this study focuses on an experimental and analytical evaluation of linear, nonlinear viscoelastic and viscoplastic responses of selected binders modified for use in WMA. The first part of the paper analyses the linear viscoelastic material properties and their ability to evaluate permanent deformation resistance. Then, the non-recoverable creep compliance parameter obtained from the Multiple Stress Creep Recovery (MSCR) test is analysed to assess the nonlinear response and permanent deformation of asphalt binders. The paper utilises a nonlinear plasto-viscoelastic (NPVE) approach to assess and quantify the nonlinear plasto-viscoelastic response of binders by separating the recoverable and irrecoverable strains measured in the MSCR test. Two WMA additives were included in this study by mixing them with polymer-modified and unmodified asphalt binders. Analysis of results showed that the NPVE approach captured a higher percentage of recovery than the NLVE approach. However, binder’s performance evaluation and ranking did not change by adopting the NPVE approach. The nonlinear viscoelastic parameters provided insight on the behaviour of asphalt binders mixed with WMA additives during loading cycles. Sasobit showed higher influence than Advera on binders in resisting permanent deformation by increasing the recoverable strain during the unloading phase.     

Novel nano polymeric system containing biosynthesized core shell silver/silica nanoparticles for functionalization of cellulosic based material

An innovative strategy for functional finishing of cellulosic based materials is based on the incorporation of a thin layer of surface modifying systems (SMS) in the form of stimuli-sensitive nanogels containing combining metal nanoparticles and silica. The silver–silica core–shell nanoparticles (NPs) were synthesized by simple one pot chemical method. Silica/silver nanoparticles have been synthesized using low concentration of dextran as reducing and stabilizing agent and using ascorbic acid as antioxidant agent. The core–shell NPs were characterized for their structural, morphological, compositional and optical behaviour using X-ray diffraction, scanning electron microscopy and energy dispersive X-ray analysis. Stimuli-responsive nanogel was prepared by copolymerization of poly(N-isopropylacrylamide) with pullulan, results in a nanogel that is responsive to both temperature and pH, the nano-particulate hydrogel of poly-NiPAAm-pullulan copolymer was synthesized using surfactant-free emulsion method. The prepared nano-particles were used during the preparation steps of the pullulan nanogel to obtain nanogel/combining metal/silica NPs to produce a composite materials. The nanoparticle size in dry (collapsed) state is estimated at 250 nm by SEM and TEM, and effect of temperature and pH on gel-nanoparticles was investigated by DLS and UV–vis spectrophotometry. The incorporation of the nanoparticles to cellulosic material was done by a simple pad dry-cure procedure from aqueous nanoparticle dispersion that contained a cross-linking agent. This application method provided sufficient integrity to coating by maintaining the responsiveness of surface modifying system. The stimuli responsiveness of modified cellulosic materials has been confirmed in terms of regulating its water uptake in dependence of pH and temperature.     

On Conducting Simultaneous Versus Sequential Engineering Activities in Risky R&D

We consider development projects in which the activities can be classified in two types: uncertainty resolving R&D efforts that accumulate in the form of knowledge to eventually give rise to a discovery; and routine technical investments which aim at improving the profitability of the project once the discovery has been made. The advantage of initiating routine preparatory activities prior to the achievement of a technological breakthrough in such projects, sometimes termed as 'concurrent engineering', is analyzed within a suitable dynamic optimization framework. The optimal double expenditure policy is compared with the conservative delayed investment policy, under which all the routine engineering activities are delayed until the risky R&D efforts culminate in a breakthrough. A criterion for the optimality of the latter policy is developed on the basis of the probability distribution of the discovery date. The application of the criterion is illustrated for a variety of specifications regarding the uncertainty associated with the R&D process. We find that simultaneous investment is the optimal policy for a large class of probability distributions. However, if the conditional probability of immediate discovery is always below some critical value, it is optimal to delay the preparatory activities until the discovery.     

A decision model for operating two alternate energy generating systems

A solar energy generating system is to be supplemented by two conventional generating systems. A method for investigating the effect of various operating policies of the combined system on the productivity and availability is developed. Using a Markov-Chain approach for computing the long-run expectations of the objectives it was demonstrated that the use of a stand-by mode for one of the conventional systems was optimal. Numerical examples are presented to demonstrate the methodology both for special and more general cases.     

A hazard function approximation used in reliability theory

The cumulative hazard function H(n) should accumulate to infinity over the distribution support, because the survivor function is Sf(n)=exp(-H(n)). The widely used approximation for the cumulative hazard function, H(n)≈Σ_k=1ⁿh(k), for a small value of the hazard function, h(k), can be useful and reasonably accurate for computing the survivor function. For the continuous case, assuming that pdf exists, the H(n) diverges as it should. For the discrete case, two examples show the use of the hazard function approximation. In example A for the uniform probability mass function, the approximation diverges. In example B for the geometric probability mass function, the approximation converges to the finite value, 1.606695, when it should be diverging. The result is surprising in light of the difference between the continuous case, pdf, and the discrete case, pmf. Thus in practice, the approximation must be used with caution     

Speech recognition in living rooms: Integrated speech enhancement and recognition system based on spatial,spectral and temporal modeling of sounds

Research on noise robust speech recognition has mainly focused on dealing with relatively stationary noise that may differ from the noise conditions in most living environments. In this paper, we introduce a recognition system that can recognize speech in the presence of multiple rapidly time-varying noise sources as found in a typical family living room. To deal with such severe noise conditions, our recognition system exploits all available information about speech and noise; that is spatial (directional), spectral and temporal information. This is realized with a model-based speech enhancement pre-processor, which consists of two complementary elements, a multi-channel speech–noise separation method that exploits spatial and spectral information, followed by a single channel enhancement algorithm that uses the long-term temporal characteristics of speech obtained from clean speech examples. Moreover, to compensate for any mismatch that may remain between the enhanced speech and the acoustic model, our system employs an adaptation technique that combines conventional maximum likelihood linear regression with the dynamic adaptive compensation of the variance of the Gaussians of the acoustic model. Our proposed system approaches human performance levels by greatly improving the audible quality of speech and substantially improving the keyword recognition accuracy.     

A scheduling model for multirobot assembly cells

We propose a mixed 0–1 linear programming model for repetitive scheduling of multirobot assembly and machining cells. The approach adopted is monolithic as opposed to hierarchical to avoid system suboptimization. The model permits any number of alternative ways (or modes) to perform each operation. A mode of an operation is determined by the required resources (facilities) and the duration of their use. The model incorporates facility changeover times. Robot collisions are avoided. Several objective functions are formulated to support different purposes. The scheduling problem of a multirobot assembly cell is formulated and solved by using commercially available mathematical programming software. Solutions under four different objective functions are reported.Acknowledging the complexity and considerable size of the formulation required, we prescribe and illustrate specific methods to achieve size reduction. Finally, for successful use of our model, an information processing schema is offered as a general guidance to help data management needed by the model.     

Operating and maintenance policies of a service system

In this paper we analyze the effects of various nonoptimal operating maintenance policies on the level of service provided by a system of $\text{N}$ units, $\text{M}$ of which need to be in continuous operation. It is shown that policies that utilize the units' characteristics are more efficient than first in first out (FIFO) or random policies. A comparison between these policies and an optimal one is made with respect to small systems. Furthermore, the problem of assigning priorities in such systems is discussed.