Application of the LMS algorithm to identify the surface velocity responsible for the radiated sound pressure

A time domain approach based on the least mean square (LMS) algorithm is applied to reconstruct the source amplitude and source distribution on a plate. For this a numerical experiment is established. A boundary element model is used to calculate the required impulse response functions describing the pressure in near- and far-field for a given volume flow at individual patches on the plate. Three different cases are considered. Firstly, a volume flow is given to a single patch. The LMS algorithm is used to reconstruct the source signal by means of receiving positions in the far-field. Secondly, the approach is used to identify the vibration pattern and source signal on a line of patches. Thirdly, a vibration pattern was given to the plate as the whole. For the reconstruction an assumption was made about the underlying vibration patterns (e.g. expansion in vibrational modes). Such an approach proved to be very time efficient and powerful. It also showed the need to place the receiving positions in the near-field to be able to obtain correct results over the whole frequency range. However, this is not a problem of the approach based on the LMS algorithm, but just due to the underlying physics. It is not possible to deduce the near-field from far-field observations, and therefore the vibrations mainly leading to a near-field are simply not visible in the far-field

A Mechanics Based Surface Image Interpretation Method for Multifunctional Nanocomposites

Graphene nanosheets and thicker graphite nanoplatelets are being used as reinforcement in polymeric materials to improve the material properties or induce new functional properties. By improving dispersion, de-agglomerating the particles, and ensuring the desired orientation of the nano-structures in the matrix, the microstructure can be tailored to obtain specific material properties. A novel surface image assisted modeling framework is proposed to understand functional properties of the graphene enhanced polymer. The effective thermal and mechanical responses are assessed based on computational homogenization. For the mechanical response, the 2-D nanoplatelets are modeled as internal interfaces that store energy for membrane actions. The effective thermal response is obtained similarly, where 2-D nanoplatelets are represented using regions of high conductivity. Using the homogenization simulation, macroscopic stiffness properties and thermal conductivity properties are modeled and then compared to the experimental data. The proposed surface image assisted modeling yields reasonable effective mechanical and thermal properties, where the Kapitza effect plays an important part in effective thermal properties

Fuel consumption and friction benefits of low viscosity engine oils for heavy duty applications

[EN] One of the most attractive ways to tackle vehicle engine's inefficiencies is the use of Low Viscosity Engine Oils (LVEO). Adopted some decades ago for their use in the Light Duty segment, LVEO are now reaching the Heavy Duty segment. In this study, a comparative fuel consumption test, where a LVEO performance is evaluated on an urban compressed natural gas buses fleet is portrayed. Then the friction performance of the same oils are studied on a Cameron-Plint tribometer, on an adapted twin disc tribometer to simulate journal bearing friction and on a Ball-on-Disc rig, using real engine parts in the former and the same set of engine oils used during the fleet test. Results show a fuel consumption reduction in the fleet test and corresponding friction reduction in the tribometers when LVEO are used.The authors wish to express their gratitude to the Spanish "Ministerio de Economia y competitividad- Direccion General de Investigacion Cientifica y Tecnica" for supporting the EFICOIL project (TRA2015-70785-R), the Colombian "Departamento Administrativo de Ciencia, Tecnologia e Innovacion Colciencias" (C646-2014) and the Norrbottens Research Council for financial support ("NoFo14-210").Tormos, B.; Ramirez-Roa, LA.; Johansson, J.; Bjorling, M.; Larsson, R. (2017). Fuel consumption and friction benefits of low viscosity engine oils for heavy duty applications. Tribology International. 110:23-34. https://doi.org/10.1016/j.triboint.2017.02.007S233411

A scientific perspective on reducing ski-snow friction to improve performance in Olympic Cross-Country Skiing, the Biathlon and Nordic Combined

Of the medals awarded at the 2022 Winter Olympics in Beijing, 24% were for events involving cross-country skiing, the biathlon and Nordic combined. Although much research has focused on physiological and biomechanical characteristics that determine success in these sports, considerably less is yet known about the resistive forces. Here, we specifically describe what is presently known about ski-snow friction, one of the major resistive forces. Today, elite ski races take place on natural and/or machine-made snow. Prior to each race, several pairs of skis with different grinding and waxing of the base are tested against one another with respect to key parameters, such as how rapidly and for how long the ski glides, which is dependent on ski-snow friction. This friction arises from a combination of factors, including compaction, plowing, adhesion, viscous drag, and water bridging, as well as contaminants and dirt on the surface of and within the snow. In this context the stiffness of the ski, shape of its camber, and material composition and topography of the base exert a major influence. An understanding of the interactions between these factors, in combination with information concerning the temperature and humidity of both the air and snow, as well as the nature of the snow, provides a basis for designing specific strategies to minimize ski-snow friction. In conclusion, although performance on "narrow skis" has improved considerably in recent decades, future insights into how best to reduce ski-snow friction offer great promise for even further advances

A Zoology of Bell inequalities resistant to detector inefficiency

We derive both numerically and analytically Bell inequalities and quantum measurements that present enhanced resistance to detector inefficiency. In particular we describe several Bell inequalities which appear to be optimal with respect to inefficient detectors for small dimensionality d=2,3,4 and 2 or more measurement settings at each side. We also generalize the family of Bell inequalities described in Collins et all (Phys. Rev. Lett. 88, 040404) to take into account the inefficiency of detectors. In addition we consider the possibility for pairs of entangled particles to be produced with probability less than one. We show that when the pair production probability is small, one must in general use different Bell inequalities than when the pair production probability is high.Comment: 12 pages, revtex. Appendix completed, minor revision

Homogenization Method for 2-D Nano-Structure Reinforced Polymer Matrix

Graphene flakes are used as additives in polymer matrices to improve the material properties. Critical aspects of obtaining graphene enhanced functional properties in polymer nanocomposites include the composition and morphological optimization. The concentrations of flakes must be optimized to create components’ material properties which achieve the target design and cost. Via processing, the microstructure can be tailored to attain the desired material properties by de-agglomerating the particles, improving dispersion and, ensuring the desired orientation of the nano-structures in the matrix. A predictive model is needed to understand the increased stiffness of the reinforced matrix of these composite materials. Using a 2D image and FE representation of micrographs of polyethylene (PE) embedded with (2-D) graphite nanoplatelets obtained via melt extrusion, the mechanical properties are assessed based on computational homogenization. A representative volume element (RVE) of the nano-structure reinforced polymer matrix is established, where the PE bulk and 2-D flakes are modeled based on their elastic properties. The 2-D flakes are considered as internal interfaces that store energy for membrane actions. From the homogenization analysis, macroscopic stiffness properties are simulated and compared to the experimental of Gaska et al. [1] with respect to increasing volume concentrations, orientation and distribution of the graphene. References: [1] Gaska et al., (2017) Gas Barrier, Thermal, Mechanical and Rheological Properties of Highly Aligned Graphene-LDPE Nanocomposites, Polymers 9, 294

Self-powered, long-durable, and highly selective oil–solid triboelectric nanogenerator for energy harvesting and intelligent monitoring

Triboelectric nanogenerators (TENGs) have potential to achieve energy harvesting and condition monitoring of oils, the “lifeblood” of industry. However, oil absorption on the solid surfaces is a great challenge for oil–solid TENG (O-TENG). Here, oleophobic/superamphiphobic O-TENGs are achieved via engineering of solid surface wetting properties. The designed O-TENG can generate an excellent electricity (with a charge density of 9.1 µC m−2 and a power density of 1.23 mW m−2), which is an order of magnitude higher than other O-TENGs made from polytetrafluoroethylene and polyimide. It also has a significant durability (30,000 cycles) and can power a digital thermometer for self-powered sensor applications. Further, a superhigh-sensitivity O-TENG monitoring system is successfully developed for real-time detecting particle/water contaminants in oils. The O-TENG can detect particle contaminants at least down to 0.01 wt% and water contaminants down to 100 ppm, which are much better than previous online monitoring methods (particle > 0.1 wt%; water > 1000 ppm). More interesting, the developed O-TENG can also distinguish water from other contaminants, which means the developed O-TENG has a highly water-selective performance. This work provides an ideal strategy for enhancing the output and durability of TENGs for oil–solid contact and opens new intelligent pathways for oil–solid energy harvesting and oil condition monitoring

Real-Time Monitoring of Cable Break in a Live Fiber Network using a Coherent Transceiver Prototype

We monitor a 524km live network link using an FPGA-based sensing-capable coherent transceiver prototype during a human-caused cable break. Post-analysis of polarization data reveals minute-level potential warning precursors and baseline-exceeding changes directly preceding the break.Comment: 3 page