NUMERICAL-ANALYTICAL MODEL OF THE LUMINANCE FACTOR OF AN ARBITRARY SURFACE

Road safety is determined by the distribution of luminance created by asphalt concrete surfaces. On the one hand, experimental determination of the bidirectional reflectance distribution function is laborious, on the other hand, for some angles this task is difficult. The authors propose to use both analytical and statistical models of the luminance factor, which allow determining the luminance factors or coefficients for arbitrary angles of incidence and sighting. The models are based on the idea of a plane-parallel layer, in the volume of which radiation scattering occurs. With correctly selected optical properties of the layer (the optical thickness of the medium, the albedo of single scattering, the phase function of the particles included in the composition), the models allow obtaining reliable results, which was confirmed when compared with the measurement results. The models can also be applicable not only for asphalt concrete pavements, but also for any other surfaces.

Fully developed anelastic convection with no-slip boundaries

Anelastic convection at high Rayleigh number in a plane parallel layer with no slip boundaries is considered. Energy and entropy balance equations are derived, and they are used to develop scaling laws for the heat transport and the Reynolds number. The appearance of an entropy structure consisting of a well-mixed uniform interior, bounded by thin layers with entropy jumps across them, makes it possible to derive explicit forms for these scaling laws. These are given in terms of the Rayleigh number, the Prandtl number and the bottom to top temperature ratio, which also measures how much the density varies across the layer. The top and bottom boundary layers are examined and they are found to be very different, unlike in the Boussinesq case. Elucidating the structure of these boundary layers plays a crucial part in determining the scaling laws. Physical arguments governing these boundary layers are presented, concentrating on the case in which the boundary layers are so thin that temperature and density vary little across them, even though there may be substantial temperature and density variations across the whole layer. Different scaling laws are found, depending on whether the viscous dissipation is primarily in the boundary layers or in the bulk. The cases of both high and low Prandtl number are considered. Numerical simulations of no-slip anelastic convection up to a Rayleigh number of $10^7$ have been performed and our theoretical predictions are compared with the numerical results.

Thalamus and claustrum control parallel layer 1 circuits in retrosplenial cortex

The granular retrosplenial cortex (RSG) is critical for both spatial and non-spatial behaviors, but the underlying neural codes remain poorly understood. Here, we use optogenetic circuit mapping in mice to reveal a double dissociation that allows parallel circuits in superficial RSG to process disparate inputs. The anterior thalamus and dorsal subiculum, sources of spatial information, strongly and selectively recruit small low-rheobase (LR) pyramidal cells in RSG. In contrast, neighboring regular-spiking (RS) cells are preferentially controlled by claustral and anterior cingulate inputs, sources of mostly non-spatial information. Precise sublaminar axonal and dendritic arborization within RSG layer 1, in particular, permits this parallel processing. Observed thalamocortical synaptic dynamics enable computational models of LR neurons to compute the speed of head rotation, despite receiving head direction inputs that do not explicitly encode speed. Thus, parallel input streams identify a distinct principal neuronal subtype ideally positioned to support spatial orientation computations in the RSG.

DETERMINATION OF PIROCARBON MATRIX CHARACTERISTICS IN CARBON/CARBON COMPOSITES

One of the methods of carbon/carbon composites (C/C composites) production is the deposition of a pyrocarbon (pyC) matrix in a porous preform. The investigation of the pyC matrix characteristics is based on the optical anisotropy with determination of the extinction angle Ae and X-ray diffraction determination of the interplanar spacing d002, crystallite size in the direction of stacking of graphite layers Lc and average size of graphite planes parallel layer in crystallites La. In this study, three previously produced by the thermal gradient method with different parameters specimens of C/C composites were investigated by optical microscopy and X-ray diffraction methods. The studied specimens have a different type of a texture and different structural characteristics of the pyC matrix. Extinction angle Ae for specimen 1, specimen 2 and 3 was 5°, 19° and 41°, respectively. The range of the extinction angle for the pyC matrix is wider than that presented in literature. And according to the classification of pyC the matrix of specimen 1, specimen 2 and 3 is dark laminar pyC, rough laminar pyC and highly textured pyC. For specimen 2 the largest d002 equal to 0.3476 nm was observed. The lowest degree of three-dimensional ordering relative other specimens was for the specimen 2 with rough laminar pyC matrix. The highest degree of three-dimensional ordering was for the specimen 3 with highly textured pyC matrix. However, there is no direct relationship between the textural and structural characteristics of the pyC matrix. Therefore, the study of the pyC matrix should be based on optical and X-ray diffraction methods.

Battery State of Health Estimation with Improved Generalization Using Parallel Layer Extreme Learning Machine

The online estimation of battery state of health (SOH) is crucial to ensure the reliability of the energy supply in electric and hybrid vehicles. An approach for enhancing the generalization of SOH estimation using a parallel layer extreme learning machine (PL-ELM) algorithm is analyzed in this paper. The deterministic and stable PL-ELM model is designed to overcome the drift problem that is associated with some conventional machine learning algorithms; hence, extending the application of a single SOH estimation model over a large set of batteries of the same type. The PL-ELM model was trained with selected features that characterize the SOH. These features are acquired as the discrete variation of indicator variables including voltage, state of charge (SOC), and energy releasable by the battery. The model training was performed with an experimental battery dataset collected at room temperature under a constant current load condition at discharge phases. Model validation was performed with a dataset of other batteries of the same type that were aged under a constant load condition. An optimum performance with low error variance was obtained from the model result. The root mean square error (RMSE) of the validated model varies from 0.064% to 0.473%, and the mean absolute error (MAE) error from 0.034% to 0.355% for the battery sets tested. On the basis of performance, the model was compared with a deterministic extreme learning machine (ELM) and an incremental capacity analysis (ICA)-based scheme from the literature. The algorithm was tested on a Texas F28379D microcontroller unit (MCU) board with an average execution speed of 93 μs in real time, and 0.9305% CPU occupation. These results suggest that the model is suitable for online applications.

Study on Microstructure Differences of Coal Samples before and after Loading

The microscopic pore structure of coal affects the content of adsorbed gas. The microstructure of coal sample before and after loading is different, which will affect the adsorption and permeability of coal seam gas. In order to study this difference, the authors carried out mercury intrusion experiments on coal containing different coal samples and used nondestructive nuclear magnetic resonance (NMR) techniques, scanning electron microscopy, and transmission electron microscopy, to study the microstructure of coal samples before and after loading. The experimental results show that the pores of coal samples are mainly micropores and small pores, and the mesopores and macropores are relatively few. The T2 spectrum area of the coal sample is significantly increased after loading, and the parallel-layer coal samples’ T2 spectrum area is 46735, which is 9112 more than the vertical layer coal samples. The T2 spectrum of the vertical coalbed of saturated water samples shows a three-peak shape, the peak of the T2 spectrum is 12692, and the parallel bedding shows a bimodal morphology. The peak area of the T2 spectrum is 11277. The permeability of the parallel bedding coal sample is good, and the coal sample exhibits anisotropic properties. The pores and cracks of the coal samples increased after loading, and the localized area of the coal sample collapsed and formed a fracture zone, which was not conducive to the occurrence of coal seam gas. Further explanation of the changes in the permeability of the coal sample before and after loading will affect the gas storage and transportation.

Thalamus and claustrum control parallel layer 1 circuits in retrosplenial cortex

ABSTRACTThe granular retrosplenial cortex (RSG) is critical for both spatial navigation and fear conditioning, but the neural codes enabling these seemingly disparate functions remain unknown. Here, using optogenetic circuit mapping, we reveal a double dissociation that allows parallel circuits in superficial RSG to process navigation- versus fear-related inputs. The anterior thalamus, a source of head direction information, strongly recruits small, low rheobase (LR) pyramidal cells in RSG layer 3. Neighboring regular-spiking (RS) cells are instead preferentially controlled by claustral and anterior cingulate inputs, sources of higher-order and fear-related information. Precise sublaminar axonal and dendritic arborization within RSG layer 1 enable this parallel processing. Synaptic dynamics and computational modeling suggest LR neurons are optimally-tuned conjunctive encoders of direction and distance inputs from the thalamus and dorsal subiculum, respectively. RS cells are better positioned to support contextual fear memories. Thus, parallel input streams to computationally-distinct principal neurons help facilitate diverse RSG functions.

FLiES-SIF version 1.0: three-dimensional radiative transfer model for estimating solar induced fluorescence

Global terrestrial ecosystems control the atmospheric CO2 concentration through gross primary production (GPP) and ecosystem respiration processes. Chlorophyll fluorescence is one of the energy release pathways of excess incident light in the photosynthetic process. Over the last 10 years, extensive studies have revealed that canopy-scale Sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf-level photosynthesis to global GPP, can be observed from satellites. SIF is used to infer photosynthetic capacity of plant canopy; however, it is not clear how the leaf-level SIF emission contributes to the top-of-canopy directional SIF. Plant canopy radiative transfer models are useful tools to understand the mechanism of anisotropic light interactions such as scattering and absorption in plant canopies. One-dimensional (1-D) plane-parallel layer models (e.g., the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model) have been widely used and are useful to understand the general mechanisms behind the temporal and seasonal variations in SIF. However, a 1-D model does not explain the complexity of the actual canopy structures. Three-dimensional models (3-D) have a potential to delineate the realistic directional canopy SIFs. Forest Light Environmental Simulator for SIF (FLiES-SIF) version 1.0 is a 3-D Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind the SIF emission from complex forest canopies. The FLiES-SIF model is coupled with leaf-level fluorescence and a physiology module so that users are able to simulate how the changes in environmental and leaf traits as well as canopy structure affect the observed SIF at the top of the canopy. The FLiES-SIF model was designed as three-dimensional model, yet the entire modules are computationally efficient: FLiES-SIF can be easily run by moderate-level personal computers with lower memory demands and public software. In this model description paper, we focused on the model formulation and simulation schemes, and showed some sensitivity analysis against several major variables such as view angle and leaf area index (LAI). The simulation results show that SIF increases with LAI then saturated at LAI>2–4 depending on the spectral wavelength. The sensitivity analysis also shows that simulated SIF radiation may decrease with LAI at a higher LAI domain (LAI>5). These phenomena are seen in certain Sun and view angle conditions. This type of nonlinear and nonmonotonic SIF behavior towards LAI is also related to spatial forest structure patterns. FLiES-SIF version 1.0 can be used to quantify the canopy SIF in various view angles including the contribution of multiple scattering which is the important component in the near-infrared domain. The potential use of the model is to standardize the satellite SIF by correcting the bidirectional effect. This step will contribute to the improvement of the GPP estimation accuracy through SIF.

Redetermination and new description of the crystal structure of vanthoffite, Na6Mg(SO4)4

The crystal structure of vanthoffite {hexasodium magnesium tetrakis[sulfate(VI)]}, Na6Mg(SO4)4, was solved in the year 1964 on a synthetic sample [Fischer & Hellner (1964). Acta Cryst. 17, 1613]. Here we report a redetermination of its crystal structure on a mineral sample with improved precision. It was refined in the space group P21/c from a crystal originating from Surtsey, Iceland. The unique Mg (site symmetry \overline{1}) and the two S atoms are in usual, only slightly distorted octahedral and tetrahedral coordinations, respectively. The three independent Na atoms are in a distorted octahedral coordination (1×) and distorted 7-coordinations intermediate between a `split octahedron' and a pentagonal bipyramid (2×). [MgO6] coordination polyhedra interchange with one half of the sulfate tetrahedra in <011> chains forming a (100) meshed layer, with dimers formed by edge-sharing [NaO7] polyhedra filling the interchain spaces. The other [NaO7] polyhedra are organized in a parallel layer formed by [010] and [001] chains united through edge sharing and bonds to the remaining half of sulfate groups and to [NaO6] octahedra. The two types of layers interconnect through tight bonding, which explains the lack of morphological characteristics typical of layered structures.

FLiES-SIF ver. 1.0: Three-dimensional radiative transfer model for estimating solar induced fluorescence

Global terrestrial ecosystems control the atmospheric CO2 concentration through gross primary production (GPP) and ecosystem respiration processes. Chlorophyll fluorescence is one of the energy release pathways of excess incident lights in the photosynthetic process. Over the last ten years, extensive studies have been revealed that canopy scale sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf level photosynthesis to global GPP, can be observed from satellites. SIF is used to infer photosynthetic capacity of plant canopy, however, it is not clear how the leaf-level SIF emission contributes to the top of canopy directional SIF. Plant canopy radiative transfer models are the useful tools to understand the causality of directional canopy SIF. One dimensional (1-D) plane parallel layer models (e.g. the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model) have been widely used and are useful to understand the general mechanisms behind the temporal and seasonal variations in SIF. However, due to the lack of complexity of the actual canopy structures, three dimensional models (3-D) have a potential to delineate the realistic directional canopy SIFs. Forest Light Environmental Simulator for SIF (FLiES-SIF) version 1.0 is the 3-D Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind the SIF emission from complex forest canopies. In this model description paper, we focused on the model formulation and simulation schemes, and showed some sensitivity analysis against several major variables such as view angle and leaf area index (LAI). The simulation results show that SIF increases with LAI then saturated at LAI > 2–4 depending on the spectral wavelength. The sensitivity analysis also shows that simulated SIF radiation may decrease with LAI at higher LAI domain (LAI > 5). These phenomena are seen in certain sun and view angle conditions. This type of non-linear and non-monotonic SIF behavior to LAI is also related to spatial forest structure patterns. FLiES-SIF version 1.0 can be used to quantify the canopy SIF in various view angles including the contribution of multiple scattering which is the important component in the near infrared domain. The potential use of the model is to standardize the satellite SIF by correcting the bi-directional effect. This step will contribute to the improvement of the GPP estimation accuracy through SIF.