Explore the vast range of titles available.

Failure, damage spread and recovery crucially underlie many spatially embedded networked systems ranging from transportation structures to the human body. Here we study the interplay between spontaneous damage, induced failure and recovery in both embedded and non-embedded networks. In our model the network’s components follow three realistic processes that capture these features: (i) spontaneous failure of a component independent of the neighborhood (internal failure), (ii) failure induced by failed neighboring nodes (external failure) and (iii) spontaneous recovery of a component. We identify a metastable domain in the global network phase diagram spanned by the model’s control parameters where dramatic hysteresis effects and random switching between two coexisting states are observed. This dynamics depends on the characteristic link length of the embedded system. For the Euclidean lattice in particular, hysteresis and switching only occur in an extremely narrow region of the parameter space compared to random networks. We develop a unifying theory which links the dynamics of our model to contact processes. Our unifying framework may help to better understand controllability in spatially embedded and random networks where spontaneous recovery of components can mitigate spontaneous failure and damage spread in dynamical networks.

In this case study, machine and process variables were extracted from the process control system (Prod-IQ) and combined with tested mechanical properties of wood fiber insulation boards according to product type and time of manufacture. The boards were taken from the production line (dry process), and the internal bond strength ( σ mt ) and the compressive strength at 10% deformation ( σ 10 ) were determined according to the European Standard EN 826 and 1607. The complete data set was preprocessed and split into training and test sets using k-fold cross-validation. The performance of the random forest algorithm (RF) was evaluated with the correlation coefficient ( R ), the coefficient of determination ( R 2 ), root-mean-square error (RMSE) and mean absolute percentage error (MAPE) and compared with artificial neural networks (ANN) and support vector machines (SVM). Forward feature selection was used to reduce input dimensionality and improve the generalizability of the algorithms. All machine learning algorithms predicted the mechanical properties with high accuracy, but the RF algorithm revealed the best generalization performance ( σ mt : R  = 0.960, R 2 = 0.916, RMSE = 4.05, MAPE = 12.11; σ 10 : R  = 0.981, R 2 = 0.963, RMSE = 17.19, MAPE = 5.64). This work demonstrates that machine learning can be applied to predict relevant properties of wood fiber boards for an improved quality control in real time.

BackgroundA novel numerical method for calculating the contributions of individual diodes in a set of light emitting diodes (LEDs), aimed at simulating a blackbody radiation source, is examined. The intended purpose of the light source is to enable calibration of various types of optical sensors, particularly optical radiation pyrometers in the spectral range from 700 nm to 1070 nm.ResultsThis numerical method is used to determine and optimize the intensity coefficients of individual LEDs that contribute to the overall spectral distribution. The method was proven for known spectral distributions: “flat” spectrum, International Commission on Illumination (CIE) standard daylight illuminant D65 spectrum, Hydrargyrum Medium-arc Iodide (HMI) High Intensity Discharge (HID) lamp, and finally blackbody radiation spectra at various temperatures.ConclusionsThe method enables achieving a broad range of continuous spectral distributions and compares favorably with other methods proposed in the literature.

Motivated by the fact that many physical landscapes are characterized by long-range height-height correlations that are quantified by the Hurst exponent H , we investigate the statistical properties of the iso-height lines of correlated surfaces in the framework of Schramm-Loewner evolution (SLE). We show numerically that in the continuum limit the external perimeter of a percolating cluster of correlated surfaces with H ∈ [−1, 0] is statistically equivalent to SLE curves. Our results suggest that the external perimeter also retains the Markovian properties, confirmed by the absence of time correlations in the driving function and the fact that the latter is Gaussian distributed for any specific time. We also confirm that for all H the variance of the winding angle grows logarithmically with size.

In this work we have investigated changes in dielectric properties, electrical conductivity and complex impedance of Fe 2 TiO 5 nanopowder compacts and bulk samples as a function of elevated temperature (room to 423 K compacts, to 443 K bulk samples), frequency (100 Hz–1 MHz) and composition (starting molar ratio of Fe 2 O 3 and TiO 2 1:1—PSB11 and 1:1.5—PSB115). XRD, SEM and TEM analysis of PSB11 and PSB115 powders obtained by a simple solid state process from starting hematite and anatase nanopowders confirmed the formation of nanostructured orthorhombic pseudobrookite with small amounts of excess hematite and rutile. The dielectric constant decreased with frequency and temperature for both compacts and bulk samples. Higher values were determined for bulk samples also reflecting the influence of sample composition. Change in the dielectric loss also reflected the influence of sample composition showing one maximum at high frequencies for compacts, and two maxima at room temperature for bulk samples. Complex impedance was analyzed using equivalent circuits and showed in the case of compacts the influence of both grain and grain boundary components, while in the case of bulk samples the dominant influence of grain boundaries. The temperature dependence of the determined grain and grain boundary resistance for compacts and grain boundary resistance for bulk samples was analyzed using the adiabatic small polaron hopping model enabling determination of activation energies for conduction, while the temperature dependence of relaxation times enabled determination of activation energies for relaxation. Changes in electrical conductivity for compacts and bulk samples followed Jonscher’s power law. The change of the determined frequency constant with temperature showed that at elevated temperatures the quantum mechanical-tunneling model for the case of small polaron hopping explains the conduction mechanism occurring in both compacts and bulk samples.

Bulk samples of pseudobrookite with an orthorhombic crystal structure were prepared by sintering a mixture of starting hematite and anatase nano powders in the weight ratio 60:40 at three different sintering temperatures (950, 1050 and 1150 °C) resulting in different microstructures determined by SEM analysis. Humidity sensing properties of pseudobrookite were investigated by measuring changes in electrical properties at operating temperatures of 20, 40 and 60 °C in the frequency range 100 Hz–100 kHz in the relative humidity range 30–90% in a climatic chamber. At 100 Hz, and 20 °C the impedance of pseudobrookite sintered at 1150 °C reduced over 5 times in the humidity range 40–90%, and 7 times at 60 °C for pseudobrookite sintered at 950 °C. Detailed analysis of dielectric properties showed that the dielectric constant increased noticeably with increase in humidity at low frequencies. Electrical conductivity change with frequency followed the Jonscher power law, and increased with increase in relative humidity. The determined frequency constant reduced with increase in sample temperature and increase in relative humidity. The conduction mechanism can be explained using the correlated barrier hopping model. Analysis of complex impedance using an equivalent circuit showed the dominant influence of grain boundaries. Low hysteresis (3.6 and 2.99%) was obtained in the 40–90% humidity range at room temperature (25 °C) for pseudobrookite sintered at 950 and 1150 °C.

The vehicular mobility causes 15% of greenhouse gases emission: one million tons of carbon anhydrite per hour. In addition, it produces CO, NOx, fine powders, carcinogenic and mutagenic elements: these substances will disappear in the presence of solar vehicles. And solar mobility would also mitigate indirect effects: fuel used to transport fuel, energy for the distillation of hydrocarbons, gas leaks, even fracking, explosions, rivers and oceans. In contrast, electric and hybrid vehicles do not allow this improvement in the quality of life. In almost all modern countries, the energy mix is strongly unbalanced towards fossil fuels: massive electrification would not make mobility sustainable, but rather risks worsening its effect on the environment by shifting the problem of emissions from cities to power plants. The Sun, indeed, can guarantee long-term sustainable mobility: for every circulating solar vehicle CO2 production is really zero. From July to today, our solar racing car has travelled 3000 km, avoiding to emit half a ton of CO2: reporting these data to a conventional use, each solar vehicle would avoid the release of 1.5 tons of CO2 per year: like planting 10 large trees for each month in our garden. This study describes how to transform a solar super-car into an ordinary vehicle for urban and everyday mobility.

The present article describes the integrated path used for the conceptual, functional and constructive design of an exclusive multi-occupant solar-powered vehicle. The project was based on the massive implementation of concurrent engineering and quality tools, rarely used in such an integrated way, featuring a novel and attractive design, 3D CAD modelling, structural and fluid dynamics validations, in-scale rapid prototyping, functional tests, multi-objective optimization, parts manufacturing and assembly. Thanks to this approach, the solar car prototype presented high technological contents, especially in terms of materials, structures and processes. Furthermore, large CNC-machined multi-material molds and hybrid manufacturing solutions were adopted to speed up the production phase allowing to move from the initial concept to the final prototype within 24 months. Since June 2018, the solar vehicle is on the road transporting 4 people, weighing less than 300kg, reaching speeds of 120km/h and able to travel hundreds of kilometers with zero-emission and no fuel consumption.

In this work we have analyzed how milling starting commercial Mn–Zn powder prior to the sintering process has an influence on electrical conductivity, relative permittivity and complex impedance in the frequency range from 100 Hz to 1 GHz and relative permeability in the frequency range 1–500 MHz. Starting powders additionally were milled for 30, 60, 120 and 240 min followed by sintering disk samples between 900 and 1300 °C. Structural properties were analyzed using XRD and SEM analysis. Milling the starting powder reduced grain and crystallite size, but longer milling leads to agglomeration and consequently an inhomogeneous microstructure that was more expressed at higher sintering temperatures. Milling the starting powder improved relative permeability, reaching a maximum for samples of starting powder milled for 60 min and sintered at 1200 °C.

Many examples of natural systems can be described by random Gaussian surfaces. Much can be learned by analyzing the Fourier expansion of the surfaces, from which it is possible to determine the corresponding Hurst exponent and consequently establish the presence of scale invariance. We show that this symmetry is not affected by the distribution of the modulus of the Fourier coefficients. Furthermore, we investigate the role of the Fourier phases of random surfaces. In particular, we show how the surface is affected by a non-uniform distribution of phases.