Conventional Power Law Research Articles

The IMSCal approach to determine collision cross section of multiply charged anions in traveling wave ion mobility spectrometry

The need for appropriate standards to calibrate ion arrival times in traveling wave ion mobility (TWIM) remains an issue for collision cross section (CCS) measurements, particularly in the case of multiply charged anions due to the scarcity of calibrants in the negative ion mode. In order to circumvent constraints raised for standards in the conventional power law calibration, the new approach recently implemented in the IMSCal software (Anal. Chem. 93 (2021) 3542–3550) has been evaluated here to derive CCS of multiply charged anions measured by TWIM. The mathematical model developed in IMSCal to describe ion motion in the TWIM cell was trained with different combinations of phosphoric acid clusters and deprotonated polyalanine standards and performance of so-obtained calibrations was evaluated for multiply deprotonated oligothymidine 10mers used as control analytes. Although optimal composition of the calibrant set could not be fully rationalized, one mandatory condition for best CCS accuracy is to include standards of different charge states to properly model the effects of radial distribution of ions in the TWIM cell. Further improvement of calibration robustness requires that one of these charge states equals that of the analytes to account for the effects of velocity relaxation also incorporated in the IMSCal model. Doing so, experimental CCS values could be readily obtained with relative error below ±5% for anions of charge state up to 6–.

Vertical extrapolation of Advanced Scatterometer (ASCAT) ocean surface winds using machine-learning techniques

Abstract. The increasing demand for wind energy offshore requires more hub-height-relevant wind information, while larger wind turbine sizes require measurements at greater heights. In situ measurements are harder to acquire at higher atmospheric levels; meanwhile the emergence of machine-learning applications has led to several studies demonstrating the improvement in accuracy for vertical wind extrapolation over conventional power-law and logarithmic-profile methods. Satellite wind retrievals supply multiple daily wind observations offshore, however only at 10 m height. The goal of this study is to develop and validate novel machine-learning methods using satellite wind observations and near-surface atmospheric measurements to extrapolate wind speeds to higher heights. A machine-learning model is trained on 12 years of collocated offshore wind measurements from a meteorological mast (FINO3) and space-borne wind observations from the Advanced Scatterometer (ASCAT). The model is extended vertically to predict the FINO3 vertical wind profile. Horizontally, it is validated against the NORwegian hindcast Archive (NORA3) mesoscale model reanalysis data. In both cases the model slightly over-predicts the wind speed with differences of 0.25 and 0.40 m s−1, respectively. An important feature in the model-training process is the air–sea temperature difference; thus satellite sea surface temperature observations were included in the horizontal extension of the model, resulting in 0.20 m s−1 differences with NORA3. A limiting factor when training machine-learning models with satellite observations is the small finite number of daily samples at discrete times; this can skew the training process to higher-/lower-wind-speed predictions depending on the average wind speed at the satellite observational times. Nonetheless, results shown in this proof-of-concept study demonstrate the limited applicability of using machine-learning techniques to extrapolate long-term satellite wind observations when enough samples are available.

Robust quantum Griffiths singularity above 1.5 K in nitride thin films

Quantum Griffiths singularity (QGS), which is closely correlated with the quenched disorder, is characterized by the divergence of the dynamical critical exponent and the presence of activated scaling behavior. Typically such a quantum phenomenon is rather rare and only observed in extremely low temperatures. Here we report the experimental observation of a robust QGS in nitride thin films, NbN, which survives in a rather high temperature range. The electrical transport propertied were measured under the magnetic field up to 12 T. The field induced superconductor-metal transitions were observed with the continuously changed transition points with the decrease of temperature. The dynamical critical exponent based on the conventional power-law scaling reveals a divergent trend when approaching the the low temperature limit. Moreover, the temperature and field dependence of sheet resistance can be described by the activated scaling analysis in the temperature region up to 1.6 K $\leq T \leq$ 4.0 K. We argue that the robustness of QGS in the present system originates from the Pauli paramagnetic effect due to the strong coupling between the magnetic field and the spin degree of freedom.

2D heterogeneous model of a polytropic methanation reactor

The paper presents a heterogeneous 2D model of a polytropic fixed bed methanation reactor for Co-SOEC syngas. The reactor with 80 mm inner diameter is operated without active cooling. Lab-scale experiments were used for model validation under variation of gas hourly space velocity (GHSV) (2000 h-1, 4000 h-1, 6000 h-1 and 8000 h-1) and pressure (1 bar, 2 bar, 4 bar, 6 bar, 8 bar, 10 bar). The conversion of Co-SOEC syngas containing a mixture of H2, CO and CO2 was calculated based on a two-step methanation kinetic model. Effective methanation kinetics was implemented based on a novel approximation of two different reaction efficiency approaches. The catalytic efficiency approximation combines conventional power law related and a Langmuir-Hinshelwood type reaction efficiency correlation by Roberts and Satterfield. It was found that mass transfer limitation is substantial for highly temperature sensitive polytropic methanation reactor modelling. Despite high exothermic behaviour without active cooling, a stable model set-up was managed entirely without parameter fitting to experimental data for a naturally cooled methanation reactor with highly reactive and undiluted syngas feed. The modelled results of Co-SOEC syngas methanation agree well with the experiments over a wide variety of pressure and GHSV. The interaction and limiting factors of mass diffusion, reaction heat removal, kinetics and thermodynamics can be thoroughly analysed based on the established model, which is a key step for developing highly efficient methanation reactor systems in industrial scale.

Detecting and comparing extinction debts of amphibians in different habitats of southwestern China

As a global biodiversity hotspot, southwestern China has been increasingly disturbed by human activities and has been undergoing rapid urbanization in recent years. In order to provide recommendations for conservation strategies, this paper explores the disequilibrium between land use and amphibian diversity. Four types of suitable habitat that are suitable for amphibians to inhabit (including farmland, woodland, grassland, and water habitat) were assessed and compared. Through fitting 20 models for species–area relationships (SARs), we found that different habitat types had different best-fitted SAR models. However, the conventional power law model had the advantage of being estimated without extreme values, and the estimation usually did not involve numerical problems. As such, we compared the debt mapping patterns derived from the best-fit SAR models and the power models. Regardless of the SAR models used, current amphibian richness was more strongly correlated with the past habitat area, suggesting that amphibian extinction debt existed in the region. Distribution of debt magnitude in different habitats presented congruent results: 1) The debt magnitude predicted in different habitats varied in decreasing order with grassland, water habitats, woodland, and farmland. 2) Debt magnitude in the region near the Chengdu Plain was high, while the extinction debt magnitude in the western region near the Qinghai-Tibet Plateau was low. This followed expectations, as there is a profound impact of human activities in the Chengdu Plain that threatens the survival of amphibian species in that area. In summary, our results suggest that some specific habitats (grasslands and water) and areas (Chengdu Plain) need greater conservation effort to better protect the habitats of amphibians and reduce the extinction risks of species.

Hot deformation behavior of micro-alloyed steel using processing maps developed with different constitutive equations

The hot workability of microalloyed steel was studied in the deformation temperature range of 850?1200?C and strain rate of 0.001-100s-1. The constitutive relation of flow stress with temperature, strain rate and strain was established to construct processing maps of the microalloyed steel. The processing maps were constructed using conventional power law, integral method, and Arrhenius equations. The developed processing maps were used to predict the optimal hot deformation conditions and were validated with metallurgical examinations. The safe regime for hot working of the experimental steel was found to be in the intermediate temperature-strain rate range (1000-1150?C;0.001-10 s-1), where the deformation process was dominated by dynamic recrystallization and dynamic recovery of the austenitic phase. The processing map constructed using Arrhenius equations increased continuously with an increase in deformation temperature and decrease in strain rate and it did not reveal relevant information of hot workability with respect to deformation temperature and strain rate. The dynamic recrystallization behavior of experimental steel was affected by both deformation temperature and strain rate which was explained in detail through microstructural examination.

Vertical wind speed extrapolation: Modelling using a response surface methodology (RSM) based on unconventional designs

The main objective of this paper is to develop a predictive model of vertical wind speed profile. Response surface methodology (RSM) is used for this purpose. RSM is a set of statistical and mathematical techniques useful for the development, improvement and optimisation of processes. It is mainly used in industrial processes and is successfully applied in this paper to model the wind speed at the hub height of the wind turbine. An unconventional model is adopted due to the nature of the input parameters which cannot be controlled or modified. The model validation indicators, namely correlation coefficient ([Formula: see text]) and root mean square error (RMSE = 1.02), give excellent results when comparing predicted and measured wind speeds. For the same data, the RSM model gives a better RMSE compared to the conventional power law and the artificial neural network.

Inverse Power Law based Inclusive Life Model for DC Polarity Reversal Stresses

In this paper, carefully designed experiments are reported, which indicate that the change in frequency of voltage polarity reversals results in a change in slope of v-t characteristics on the inverse power law. The power law parameters are shown to be systematic functions of frequency of polarity reversals. Based on these results, the authors propose a comprehensive inverse power law for DC polarity reversal stress application, in place of conventional inverse power law. The proposed modification is examined with experimental data of authors apart from that available in literature and found to be working well. The model provides the maximum frequency of a reversal for maximizing the life of power equipment which may pave the way for deciding on the maximum frequency of voltage reversals.

Study of the densification and grain growth mechanisms occurring during spark plasma sintering of different submicronic yttria-stabilized zirconia powders

Densification and grain growth mechanisms of Yttria-Stabilized Zirconia sintered by Spark Plasma Sintering are investigated. Sintering trajectories of four commercial submicronic powders with different average particle sizes and yttria amounts have been established and sintering regimes determined. Densification mechanisms are determined in the regime where densification is occurring without grain growth using a model derived from hot-pressing. Grain growth mechanisms are determined using the conventional power law in the regime where ceramics are fully densified. Densification occurs by grain boundary sliding accommodated by an in-series interface-reaction/lattice diffusion of cations or by an overlapping of surface diffusion and grain boundary sliding mechanisms for tetragonal stabilized zirconia and by dislocation climbing for fully stabilized zirconia. A normal grain growth occurs for each ceramic, all composed of a single phase, contrary to the two-phased ceramics obtained in literature where grain growth occurs by segregation at grain boundaries.

The importance of round-robin validation when assessing machine-learning-based vertical extrapolation of wind speeds

Abstract. The extrapolation of wind speeds measured at a meteorological mast to wind turbine rotor heights is a key component in a bankable wind farm energy assessment and a significant source of uncertainty. Industry-standard methods for extrapolation include the power-law and logarithmic profiles. The emergence of machine-learning applications in wind energy has led to several studies demonstrating substantial improvements in vertical extrapolation accuracy in machine-learning methods over these conventional power-law and logarithmic profile methods. In all cases, these studies assess relative model performance at a measurement site where, critically, the machine-learning algorithm requires knowledge of the rotor-height wind speeds in order to train the model. This prior knowledge provides fundamental advantages to the site-specific machine-learning model over the power-law and log profiles, which, by contrast, are not highly tuned to rotor-height measurements but rather can generalize to any site. Furthermore, there is no practical benefit in applying a machine-learning model at a site where winds at the heights relevant for wind energy production are known; rather, its performance at nearby locations (i.e., across a wind farm site) without rotor-height measurements is of most practical interest. To more fairly and practically compare machine-learning-based extrapolation to standard approaches, we implemented a round-robin extrapolation model comparison, in which a random-forest machine-learning model is trained and evaluated at different sites and then compared against the power-law and logarithmic profiles. We consider 20 months of lidar and sonic anemometer data collected at four sites between 50 and 100 km apart in the central United States. We find that the random forest outperforms the standard extrapolation approaches, especially when incorporating surface measurements as inputs to include the influence of atmospheric stability. When compared at a single site (the traditional comparison approach), the machine-learning improvement in mean absolute error was 28 % and 23 % over the power-law and logarithmic profiles, respectively. Using the round-robin approach proposed here, this improvement drops to 20 % and 14 %, respectively. These latter values better represent practical model performance, and we conclude that round-robin validation should be the standard for machine-learning-based wind speed extrapolation methods.

BTI saturation and universal relaxation in SiC power MOSFETs

This work focuses on the positive bias temperature instability of SiC-based MOSFETs under different stress voltages and temperatures. Stress experiments demonstrate that the threshold voltage shift (∆Vth) does not follow a conventional power law for long stress time, but exhibits a saturating log- time dependence attributed to the charge trapping in the pre-existing defects at the SiC/SiO2 interface or in the SiO2 layer. The maximum Vth shift (∆Vmax), which is a function of the total trap density, increases with the stress voltage (Vstress) and decreases for temperatures higher than 50 °C. The time constant of the traps (τ0) also shows an uptrend with Vstress with a maximum value of around 50 °C. Moreover, the trap energy distribution (γ) slightly increases with temperature. The recovery analysis shows that an empiric universal relaxation function well describes the data with a dispersion parameter (β) that follows the Arrhenius law. Finally, the Vth recovery, after the same Vstress, is enhanced with temperature and also depicts a linear behavior on the Arrhenius plot. This indicates that the charge de-trapping process is thermally activated and explains the low degradation observed at high temperatures during the stress phase.

Resistivity of Fe Al Multilayered Thin Films from Low Temperature to Room Temperature

By using electron beam gun and thermal deposition techniques in the vacuum range 6 x10-5mbar. The pure materials of 99.99% purity of iron and aluminium multilayers films grown on glass substrates at 300K in the following viz. The resistance was measured using four probe method at UGC-DAE Consortium Indore (4.2K to 300K) later resistivity, conductivity, temperature co-efficient of resistance (TCR), residual resistivity ratio (RRR) , and activation energy(Ea) were calculated. The resistivity behavior shown that the resistivity is increased with increasing the n value, resistivity is increased with increasing temperature. The data belonging to metallic region has been analyzed using the conventional power law’s and it is first time this set of films have explore resistivity at low temperature

Three-dimensional scour simulations with a two-phase flow model

In this contribution, a three-dimensional sediment scour model based on the two-phase flow Eulerian-Eulerian solver, sedFoam, is developed within the framework of the open source platform OpenFOAM. The adoption of the Eulerian approach for both fluid and sediment makes the model suitable for simulating scour process around structures with arbitrary geometry. The model is first validated with unidirectional sediment transport configurations without structures, to ensure that it can capture both flow and sediment transport processes. The validation cases show that the model can accurately simulate the sediment transport rate and bedload layer thickness as a function of the Shields number over a wide range of flow condition and sediment properties. Then, the model is applied to simulate the live-bed scour process around a vertical pile due to unidirectional current. It is a first attempt to use a two-phase model for simulating such case and its success serves as a proof-of-concept for future development. Simulated results of flow, sediment transport, and scour processes are compared with experiments and good agreement is observed. A new methodology to determine the bed shear stress in complex flow configurations is proposed. The mixture shear stress computed at the elevation of the iso-concentration ϕ0=0.08 (corresponding to top of the bedload layer) is used to define the local Shields number.Within the scour hole, a competition between fluid bed shear stress driven and gravity driven sediment transport occurs at bed angles up to β ≈ 23∘. This is lower than the repose angle (βr=32∘). The relationship between the sediment flux and the bed slope is linear below β ≈ 23∘. Above this angle the sediment flux increases nonlinearly with the bed slope while the Shields number tends to 0. This shows that, in the part of the scour hole close to the vertical cylinder, the sediment flux only result from the action of gravity: avalanching is the dominant transport mechanism and conventional power law become ineffective even with slope correction. In the lee-side of the cylinder suspended load dominant and the power law, assuming a local equilibrium between bottom shear stress and transport flux, is no longer valid. Further discussion is made on the computational cost of the proposed model and future research directions.

Low Temperature Conductivity Behaviour for Multilayered Thin Films

By using electron beam gun and thermal evaporation techniques in the vacuum range 6 x10-5mbar (V.R. Technology Bangalore Make). The pure materials of 99.99% purity of Cobalt and aluminium multilayers films were produced on glass substrates at room temperature in the following multilayered [Co10A/AL10A]N where N= 1,3,6,9 and 12 labeled as ( CA1, CA2, CA3, CA4 and CA5). The low temperature (4.2K to 300K) resistance of these samples was measured by using four probe method at UGC-DAE Consortium Indore later resistivity and conductivity calculated and temperature co-efficient of resistance (TCR), residual resistivity ratio (RRR) and activation energy (Ea) were also calculated. The resistivity behavior shown that the resistivity is increased with increasing the n value it means it increased with increasing number of layers. The data belonging to metallic region has been analyzed using the conventional power law’s it is for the first time that a set of multilayered films in the present configurations have been explored for resistivity at low temperature.

Microstructure evolution and creep behavior of high-pressure die-cast Mg–9Al–1Zn–1Sr alloy

The creep behavior of high-pressure die-cast Mg–9Al–1Zn–1Sr alloy was investigated in detail under temperatures ranging from 130 to 170 °C and stresses of 30–80 MPa. The studied alloy exhibited a high stress exponent of 8.4 and low activation energy of 102 kJ/mol. The obtained high stress exponent in studied alloy indicated the breakdown of the conventional power law. For rationalization, a threshold stress was introduced in the analysis, and then the high stress exponent was modified to be 5.2. Simultaneously, taking into account the significant influence of tested temperature on the minimum creep rate, a normalized stress exponent of 5 was achieved via the normalization method. Both methods suggested that the creep deformation of the studied alloy was mainly controlled by the dislocation climb. Moreover, transmission electron microscopy observations revealed that the origin of the threshold stress could be associated with the Orowan strengthening of γ-Mg17Al12 platelets that dynamically precipitated in Mg matrix during creep. Microstructure analysis results clarified that dislocation climb is the dominant creep mechanism of AZJ911 alloy, while the reticular eutectic Mg17Al12 phase disintegration, dynamical precipitation of γ-Mg17Al12, and twinning also influence the creep deformation of AJZ911 alloy.

Fully-CMOS Multi-Level Embedded Non-Volatile Memory Devices With Reliable Long-Term Retention for Efficient Storage of Neural Network Weights

We present a fully CMOS-compatible multi-level non-volatile memory technology, without any special process cost. It is especially suitable for storing the weights of artificial neural networks on chip with low cost, high density, and high power-efficiency. We use hot carrier injection to program the single-transistor cells, and we conduct charge pumping experiments which identify interfacial traps, rather than bulk oxide traps, as the dominant factor in producing stable $I-V$ shifts. We also derive a new physics-based experimentally verified logarithmic model to explain the rate of interfacial trap generation in large $I-V$ shift regimes where the conventional power-law no longer applies. We fabricate two chips, one using TSMC’s 16 nm FinFET and the other in 28 nm planar, and show the FinFET cells are more favorable for non-volatile memory due to their better channel control. We store multiple levels in each FinFET cell using a “program and check” strategy which sets memory cells’ currents with standard deviations less than $2~{\mu }A$ across a shifting range of over $100~{\mu }A$ . We demonstrate 8 level FinFET cells with extrapolated 10-year charge loss within 10% at 125 °C.

Fractality and Power Law Distributions: Shifting Perspectives in Educational Research

The dynamical character of education and the complexity of its constituent relationships have long been recognized, but the full appreciation of the implications of these insights for educational research is recent. Most educational research to this day tends to focus on outcomes rather than process, and rely on conventional cross-sectional designs and statistical inference methods that do not capture this complexity. This presentation focuses on two related aspects not well accommodated by conventional models, namely fractality (self-similarity, scale invariance) and power law distributions (an inverse relationship between frequency of occurrence and strength of response). Examples are presented for both phenomena based on my empirical work on of daily high school attendance rates over time. We will discuss how the statistical indicators are generated and interpreted and what they reveal about the underlying dynamics of school attendance behavior.

Elasto-Plastic Analysis of Cylindrical Vessel with Arbitrary Material Gradation Subjected to Thermo-Mechanical Loading Via DTM

For the first time, the response of the functionally graded (FG) hollow cylinder vessel with arbitrary material gradation in radial direction subjected to thermo-mechanical loads is investigated by employing differential transformation method (DTM). The coordinate transformation and proper scale factor are applied to eliminate redundant terms in DTM; as a result, fast convergence with less computational effort is observed. The elasticity modulus, thermal expansion coefficient, thermal conductivity and yield stress are assumed to be arbitrary functions of radius. The thick-walled FG reservoir is in steady-state condition, and strain hardening in plastic zone is neglected by using elastic–perfectly plastic behavior assumptions. The incompressible plastic deformation and plane-strain condition are considered to obtain radial displacement in the plastic zones. The effects of various parameters on commencement and propagation of possible plastic zones, yield pressure and yield temperature gradient are investigated. The analytical solutions for FG cylindrical container with conventional power law gradation are presented. In the case of arbitrary material gradation, the validity of the numerical procedure is proved by observing convergence and good agreement between results of DTM and results of finite element software Abaqus.

Spatial Distribution of Tourism Activities: A Polya Urn Process Model of Rank-Size Distribution

The power law is considered one of the most enduring regularities in human geography. This article aims to develop an understanding of the circumstances that may result in the power law distribution in the geography of tourism activities. The finite Polya urn process is adopted as a device to model the preferential attachment process in the flow of tourists. The model generates a rank-size distribution of tourism regions along with intuitively appealing parameters. Empirically examined using two independent sets of Australian inbound and outbound tourism data, results show that the rank-size distribution emerging from the finite Polya urn process is a superior fit to the conventional power law curve. This rank-size distribution (termed the Polya urn process model of visitor distribution) is compatible with tourist behaviors such as habit persistence and word-of-mouth effects, and can be adopted by tourism modelers to predict and efficiently summarize the spatiality of tourism.

Finite Element Simulation of High-Speed Blow Forming of an Automotive Component

High-speed blow forming (HSBF) is a new technology for producing components with complex geometries made of high strength aluminum alloy sheets. HSBF is considered a hybrid-superplastic forming method, which combines crash forming and gas blow forming. Due to its novelty, optimization of the deformation process parameters is essential. In this study, using the finite element (FE) code ABAQUS, thinning of an aluminum component produced by HSBF under different strain rates was investigated. The impact of element size, variation of friction coefficient, and material constitutive model on thinning predictions were determined and quantified. The performance of the FE simulations was validated through forming of industrial size parts with a complex geometry for the three investigated strain rates. The results indicated that the predictions are sensitive to the element size and the coefficient of friction. Remarkably, compared to a conventional power law model, the variable m-value viscoplastic (VmV) model could precisely predict the thickness variation of the industrial size component.