scholarly journals SELF v1.0: a minimal physical model for predicting time of freeze-up in lakes

2021 ◽  
Vol 14 (12) ◽  
pp. 7527-7543
Author(s):  
Marco Toffolon ◽  
Luca Cortese ◽  
Damien Bouffard
Keyword(s):  
Surface Layer ◽  
Minimal Model ◽  
General Tendency ◽  
Energy Fluxes ◽  
Statistical Characterization ◽  
Physically Based Model ◽  
Physically Based ◽  
Lake Temperature ◽  
Time Required

Abstract. Predicting the freezing time in lakes is achieved by means of complex mechanistic models or by simplified statistical regressions considering integral quantities. Here, we propose a minimal model (SELF) built on sound physical grounds that focuses on the pre-freezing period that goes from mixed conditions (lake temperature at 4 ∘C) to the formation of ice (0 ∘C at the surface) in dimictic lakes. The model is based on the energy balance involving the two main processes governing the inverse stratification dynamics: cooling of water due to heat loss and wind-driven mixing of the surface layer. They play opposite roles in determining the time required for ice formation and contribute to the large interannual variability observed in ice phenology. More intense cooling does indeed accelerate the rate of decrease of lake surface water temperature (LSWT), while stronger wind deepens the surface layer, increasing the heat capacity and thus reducing the rate of decrease of LSWT. A statistical characterization of the process is obtained with a Monte Carlo simulation considering random sequences of the energy fluxes. The results, interpreted through an approximate analytical solution of the minimal model, elucidate the general tendency of the system, suggesting a power law dependence of the pre-freezing duration on the energy fluxes. This simple yet physically based model is characterized by a single calibration parameter, the efficiency of the wind energy transfer to the change of potential energy in the lake. Thus, SELF can be used as a prognostic tool for the phenology of lake freezing.

scholarly journals SELF v1.0: A minimal physical model for predicting time of freeze-up in lakes

2021 ◽  
Author(s):  
Marco Toffolon ◽  
Luca Cortese ◽  
Damien Bouffard
Keyword(s):  
Surface Layer ◽  
Minimal Model ◽  
General Tendency ◽  
Energy Fluxes ◽  
Statistical Characterization ◽  
Physically Based Model ◽  
Physically Based ◽  
Lake Temperature ◽  
Time Required

Abstract. Predicting the freezing time in lakes is pursued by means of complex mechanistic models or by simplified statistical regressions considering integral quantities. Here, we propose a minimal model (SELF) built on sound physical grounds, which focuses on the pre-freezing period that, in dimictic lakes, goes from mixed conditions (lake temperature at 4 °C) to the formation of ice (0 °C at the surface). The model is based on the energy balance involving the two main processes governing the inverse stratification dynamics: cooling of water due to heat loss and wind-driven mixing of the surface layer. They play an opposite role in determining the time required for ice formation and contribute to the large inter-annual variability observed in ice phenology. More intense cooling, indeed, accelerates the rate of decrease of lake surface water temperature (LSWT), while stronger wind deepens the surface layer, increasing the heat capacity, and thus reduces the rate of decrease of LSWT. A statistical characterization of the process is obtained with a Monte Carlo simulation considering random sequences of the energy fluxes. The results, interpreted through an approximate analytical solution of the minimal model, elucidate the general tendency of the system, suggesting a power-law dependence of the pre-freezing duration on the energy fluxes. This simple, yet physically based model is characterized by a single calibration parameter, the efficiency of the wind energy transfer to the change of potential energy in the lake. Thus, SELF can be used as a prognostic tool for the phenology of lake freezing.

scholarly journals A new approach to mapping landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades of Washington, USA

2019 ◽  
Vol 19 (11) ◽  
pp. 2477-2495
Author(s):  
Ronda Strauch ◽  
Erkan Istanbulluoglu ◽  
Jon Riedel
Keyword(s):  
Statistical Approach ◽  
Joint Probability ◽  
North Cascades ◽  
Physically Based Model ◽  
New Approach ◽  
The North ◽  
Debris Avalanches ◽  
Landslide Hazards ◽  
Infinite Slope Stability Model ◽  
Physically Based

Abstract. We developed a new approach for mapping landslide hazards by combining probabilities of landslide impacts derived from a data-driven statistical approach and a physically based model of shallow landsliding. Our statistical approach integrates the influence of seven site attributes (SAs) on observed landslides using a frequency ratio (FR) method. Influential attributes and resulting susceptibility maps depend on the observations of landslides considered: all types of landslides, debris avalanches only, or source areas of debris avalanches. These observational datasets reflect the detection of different landslide processes or components, which relate to different landslide-inducing factors. For each landslide dataset, a stability index (SI) is calculated as a multiplicative result of the frequency ratios for all attributes and is mapped across our study domain in the North Cascades National Park Complex (NOCA), Washington, USA. A continuous function is developed to relate local SI values to landslide probability based on a ratio of landslide and non-landslide grid cells. The empirical model probability derived from the debris avalanche source area dataset is combined probabilistically with a previously developed physically based probabilistic model. A two-dimensional binning method employs empirical and physically based probabilities as indices and calculates a joint probability of landsliding at the intersections of probability bins. A ratio of the joint probability and the physically based model bin probability is used as a weight to adjust the original physically based probability at each grid cell given empirical evidence. The resulting integrated probability of landslide initiation hazard includes mechanisms not captured by the infinite-slope stability model alone. Improvements in distinguishing potentially unstable areas with the proposed integrated model are statistically quantified. We provide multiple landslide hazard maps that land managers can use for planning and decision-making, as well as for educating the public about hazards from landslides in this remote high-relief terrain.

scholarly journals Critical Review of EMC Standards for the Measurement of Radiated Electromagnetic Emissions from Transit Line and Rolling Stock

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 759
Author(s):  
Andrea Mariscotti
Keyword(s):  
Time Distribution ◽  
Communication Systems ◽  
Electromagnetic Compatibility ◽  
Transportation Systems ◽  
Operating Conditions ◽  
Rolling Stock ◽  
Intrinsic Variability ◽  
Statistical Characterization ◽  
Electromagnetic Emissions

Accurate and comprehensive methods for the assessment of radiated electromagnetic emissions in modern electric transportation systems are a necessity. The characteristics and susceptibility of modern victim signaling and communication radio services, operating within and outside the right-of-way, require an update of the measurement methods integrating or replacing the swept frequency technique with time domain approaches. Applicable standards are the EN 50121 (equivalent to the IEC 62236) and Urban Mass Transport Association (UMTA) with additional specifications from project contracts. This work discusses the standardized methods and settings, and the representative operating conditions, highlighting areas where improvements are possible and opportune (statistical characterization of measurement results, identification and distinction of emissions and line resonances, and narrowband and broadband phenomena). In particular for the Electromagnetic Compatibility (EMC) assessment with new Digital Communication Systems, the characterization of time distribution of spectral properties is discussed, e.g., by means of Amplitude Probability Distribution and including time distribution information. The problem of determination of site and setup uncertainty and repeatability is also discussed, observing on one hand the lack of clear indications in standards and, on the other hand, the non-ideality and intrinsic variability of measurement conditions (e.g., rolling stock operating conditions, synchronization issues, and electric arc intermittence).

Statistical characterization of the signal-in-space errors of the BDS: a comparison between BDS-2 and BDS-3

GPS Solutions ◽  
2021 ◽  
Vol 25 (3) ◽  
Author(s):  
Guo Chen ◽  
Renyu Zhou ◽  
Zhigang Hu ◽  
Yifei Lv ◽  
Na Wei ◽  
...  
Keyword(s):  
Statistical Characterization

New physically based model for thermal induced initial stress in 3D for silicon germanium films after deposition

2014 ◽  
Vol 33 (6) ◽  
pp. 2121-2138 ◽  
Author(s):  
Abderrazzak El Boukili
Keyword(s):  
Thermal Expansion ◽  
Initial Stress ◽  
Silicon Germanium ◽  
Rate Of Change ◽  
Thermal Mismatch ◽  
Electronic Band ◽  
Physically Based Model ◽  
Content Type ◽  
Physically Based ◽  
Pmos Transistor

Purpose – The purpose of this paper is to provide a new three dimension physically based model to calculate the initial stress in silicon germanium (SiGe) film due to thermal mismatch after deposition. We should note that there are many other sources of initial stress in SiGe films or in the substrate. Here, the author is focussing only on how to model the initial stress arising from thermal mismatch in SiGe film. The author uses this initial stress to calculate numerically the resulting extrinsic stress distribution in a nanoscale PMOS transistor. This extrinsic stress is used by industrials and manufacturers as Intel or IBM to boost the performances of the nanoscale PMOS and NMOS transistors. It is now admitted that compressive stress enhances the mobility of holes and tensile stress enhances the mobility of electrons in the channel. Design/methodology/approach – During thermal processing, thin film materials like polysilicon, silicon nitride, silicon dioxide, or SiGe expand or contract at different rates compared to the silicon substrate according to their thermal expansion coefficients. The author defines the thermal expansion coefficient as the rate of change of strain with respect to temperature. Findings – Several numerical experiments have been used for different temperatures ranging from 30 to 1,000°C. These experiments did show that the temperature affects strongly the extrinsic stress in the channel of a 45 nm PMOS transistor. On the other hand, the author has compared the extrinsic stress due to lattice mismatch with the extrinsic stress due to thermal mismatch. The author found that these two types of stress have the same order (see the numerical results on Figures 4 and 12). And, these are great findings for semiconductor industry. Practical implications – Front-end process induced extrinsic stress is used by manufacturers of nanoscale transistors as the new scaling vector for the 90 nm node technology and below. The extrinsic stress has the advantage of improving the performances of PMOSFETs and NMOSFETs transistors by enhancing mobility. This mobility enhancement fundamentally results from alteration of electronic band structure of silicon due to extrinsic stress. Then, the results are of great importance to manufacturers and industrials. The evidence is that these results show that the extrinsic stress in the channel depends also on the thermal mismatch between materials and not only on the material mismatch. Originality/value – The model the author is proposing to calculate the initial stress due to thermal mismatch is novel and original. The author validated the values of the initial stress with those obtained by experiments in Al-Bayati et al. (2005). Using the uniaxial stress generation technique of Intel (see Figure 2). Al-Bayati et al. (2005) found experimentally that for 17 percent germanium concentration, a compressive initial stress of 1.4 GPa is generated inside the SiGe layer.

Statistical characterization of engineered tissues using confocal mosaic technology

2010 ◽  
Author(s):  
David Levitz ◽  
Ardalan Ardeshiri ◽  
Jabeer Ahmed ◽  
Daniel S. Gareau ◽  
Steven L. Jacques
Keyword(s):  
Statistical Characterization ◽  
Engineered Tissues
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