Geometry-based Model Research Articles

MaaS in Bike-Sharing: Smart Phone GPS Data Based Layout Optimization and Emission Reduction Potential Analysis

As a representation of smart and green city development, bike-sharing system is one of the hottest topic in the fields of transportation, public health, urban planning, and so on. With the development of Mobility as a Service (MaaS), emerging technologies such as mobile data mining give some new solutions for optimizing bike-sharing system and predicting the emission reduction. Here, we propose a bike-sharing layout optimization and emission reduction potential analysis structure under the concept of MaaS. A human travel mode detection method and a geometry-based probability model are proposed to support the particle swarm optimization process. We implement a comparison study to analyze the computational efficiency. Taking Setagaya ward, Tokyo as the study case with about 3 million GPS trajectories, the result shows that with the increase of station number from 30 to 90, the adoption of bike-sharing system can reduce about 3.1-3.8 thousand tonnes of CO2 emission.

Path Loss Models for IEEE 802.15.4 Vehicle-to-Infrastructure Communications in Rural Areas

As a promising standard to realize low data-rate, low-power, and short-range communications among wireless devices, IEEE 802.15.4 has been widely applied in wireless sensor networks, and also been intensively investigated in vehicle-to-infrastructure (V2I) communications. In this paper, we analyze the effects of antenna height on IEEE 802.15.4 V2I communications in rural areas. In particular, we first propose a geometry-based piecewise model to quantify the variable foliage effects. Furthermore, we show the feasibility of extending foliage loss predictions from static to mobile cases with classical empirical methods. Simulation results verify the precision of our proposed channel model in rural areas by comparing it with other channel models and realistic measurements.

A simple geometry-based model for the photon

The classical and the quantum expressions of the energy of the electromagnetic radiation are compared. This comparison shows that, contrary to the commonly expected, the dependency of the energy [Formula: see text] of the photon with respect to the frequency [Formula: see text] on the Einstein–Planck relation [Formula: see text] is obtainable from classical electrodynamics, a fact that may provide a new historic perspective of the birth of quantum mechanics. It is suggested that the photon is a composite particle, constituted by quanta of electric and magnetic field fluxes maybe in an entangled state — being these two quanta either real or only as pseudo particles. It is also suggested a modification on the de Broglie’s fusion principle for the photon for the specific case in consideration.

Feasibility of using cellulose filaments as a viscosity modifying agent in self-consolidating concrete

Nanomodification of concrete represents one of the phenomenal leaps in concrete technology providing innovative tools for engineering cement composites with improved performance. In self-consolidating concrete (SCC), for instance, designing flowable–yet stable and robust–SCC mixtures requires an optimum balance between flowability and stability. This is conventionally achieved by optimizing the dosage of high range water reducing admixtures (HRWRA) indispensable for flowability, while increasing the binder content or introducing viscosity modifying agents (VMA) necessary for stability. This study shows how cellulose filaments (CF)–a new type of nanocellulose materials–can be used as a novel tool for rheology modification and strength enhancement in SCC. CF were incorporated at concentrations ranging from 0.05 to 0.30% per weight of binder in cement pastes and SCC. Rheological and mechanical properties of CF systems were compared to those of plain systems and systems incorporating a commercially available VMA of welan gum type. Results showed that CF serve as a VMA due to the buildup of flexible nanoscale CF networks. As such, a geometry-based percolation model showed that at a concentration of 0.12 wt.%, a network of percolating CF was formed. Beyond this CF content, the yield stress, the plastic viscosity, as well as the HRWRA demand exhibited a substantial increase. CF networks increased mixture viscosity–essential for stability–at low shear rates. On the other hand, at high shear rates, CF networks led to lower apparent viscosity essential for improving pumpability; owing to the streamlining of the flexible nanocellulose fibrils in the direction of flow, thereby imparting a shear thinning behavior. Furthermore, CF imparted improvement in mechanical performance of 12–26% in compression, splitting-tension, and flexure. Research outcomes are expected to contribute towards offering an alternative VMA with strength improvement potential while contributing towards the implementation of sustainable materials for concrete technology.

Geometric inhomogeneous random graphs

Real-world networks, like social networks or the internet infrastructure, have structural properties such as large clustering coefficients that can best be described in terms of an underlying geometry. This is why the focus of the literature on theoretical models for real-world networks shifted from classic models without geometry, such as Chung–Lu random graphs, to modern geometry-based models, such as hyperbolic random graphs.With this paper we contribute to the theoretical analysis of these modern, more realistic random graph models. Instead of studying directly hyperbolic random graphs, we use a generalization that we call geometric inhomogeneous random graphs (GIRGs). Since we ignore constant factors in the edge probabilities, GIRGs are technically simpler (specifically, we avoid hyperbolic cosines), while preserving the qualitative behavior of hyperbolic random graphs, and we suggest to replace hyperbolic random graphs by this new model in future theoretical studies.We prove the following fundamental structural and algorithmic results on GIRGs. (1) We provide a sampling algorithm that generates a random graph from our model in expected linear time, improving the best-known sampling algorithm for hyperbolic random graphs by a substantial factor O(n). (2) We establish that GIRGs have clustering coefficients in Ω(1), (3) we prove that GIRGs have small separators, i.e., it suffices to delete a sublinear number of edges to break the giant component into two large pieces, and (4) we show how to compress GIRGs using an expected linear number of bits.

GLONASS real-time wide-lane ambiguity resolution with an enhanced geometry-based model for medium-range baselines

Double-difference wide-lane integer ambiguities are determined first to assist narrow-lane ambiguity resolution in real-time medium-range baseline resolution. The Hatch-Melbourne-Wübbena (HMW) is the conventional strategy for wide-lane ambiguity resolution, which works well for GPS/Galileo/BDS. However, the un-canceled inter frequency bias (IFB) on double-difference measurement causes that the HMW combination is invalid on GLONASS wide-lane ambiguity resolution. The residual IFB in double-difference measurement may be several meters, especially between inhomogeneous stations. There is no effective method to model or tabulate ranging-codes IFB. In this paper, we propose a device-independent geometry-based model to achieve GLONASS real-time wide-lane ambiguity resolution for medium-range baselines. Since zenith tropospheric delay and slant ionospheric delay of satellites are estimated as unknown parameters, we utilize atmosphere-weighted algorithm to enhance the model strength and decrease the dependence on pseudorange measurement. For medium-range baseline, GLONASS wide-lane ambiguity float solutions can converge quickly by the geometry-based model. The cumulative frequency of WL AR can exceed 99% during 10 epochs. Benefiting from rapid and reliable wide-lane ambiguity resolution, the positioning accuracy of GPS/GLONASS RTK fixed solution are greater than 3 cm in level direction and 5 cm in upward direction for 40–100 km baselines. An approximately 35% improvement rate is observed in each direction compared with that of single GPS RTK. Since less available satellites for single-GLONASS mode, the convergence of wide-lane ambiguity becomes slower. For base stations with known coordinates, the enhanced geometry-based model can be developed to the enhanced geometry-fixed model and are applied to longer baselines. Assisting with the geometry-fixed model, more than 90% of GLONASS narrow-lane ambiguities can be fixed quickly for 80–160 km baselines. It should be noted that the accuracy of external atmospheric delay is critical to the performance of the geometry-based method. Its benefit may weaken with the increasing of baseline length, when external atmospheric delays are set as 0 directly.

Image processing for fractal geometry-based discrete fracture network modeling input data: A methodological approach

With the intent of making data acquisition for fractal geometry-based discrete fracture network (DFN) modeling time-efficient and automatized, a new method was established. For the automation of data retrieval from the images of the studied surfaces, a series of image-processing operations and MATLAB algorithms have been developed. The method allows the retrieval of more than 1,000 fracture-length data/cm2 of one sample in several minutes. This methodology tends to be a useful tool in studies of fracture network geometries. DFN models of a supposed excavated and/or environmental damage zone, designed with the use of data supplied by the above method, are presented in this work as an example.

Mobility Model-Based Non-Stationary Mobile-to-Mobile Channel Modeling

Non-stationary mobile-to-mobile (M2M) channel modeling has gained strong momentum as it is vital for developing M2M communications technology. Traditional geometry-based channel models (GSCMs) for M2M communications usually assume fixed velocity and moving direction, which differs from the realistic M2M scenarios and also makes it difficult to incorporate non-stationarity of channel into the regular-shaped GSCMs. In this paper, a mobility model-based method is proposed to incorporate non-stationarity into M2M channel modeling by introducing dynamic velocities and trajectories. A revised Gauss–Markov mobility model is first presented together with the cluster-based two-ring M2M reference model. The mobility model uses tuning parameters to adjust the degree of mobility randomness and covers different M2M mobility trajectories. Then, a closed-form time-variant time-frequency correlation function and the Doppler power spectrum are derived from the model. Based on the numerical analysis, it is found that for a regular-shaped GSCM with a fixed M2M scattering environment, the motion does not introduce non-stationarity, however, the dynamic motion (i.e., the changes of velocity and moving direction) leads to non-stationarity, which is reflected by the time-variant time correlation function and Doppler spectrum. Different propagation modes, cluster number, and intra-cluster nonisotropic scattering also have major impacts on channel non-stationarity. Moreover, the randomness of the mobility model is found to significantly increase the degree of channel non-stationarity. These conclusions are useful for M2M non-stationary channel simulation and communication system evaluation.

Three-Dimensional Geometry-Based UAV-MIMO Channel Modeling for A2G Communication Environments

We propose a 3-D elliptic-cylinder unmanned aerial vehicle (UAV) multiple-input-multiple-output (MIMO) channel model for air-to-ground communication environments. The mobility and altitude of UAV transmitters in the elevation plane are studied based on the proposed UAV-MIMO channel model. Furthermore, ground surface and roadside environment reflections are considered to investigate the statistical properties of the proposed UAV-MIMO channel model. Finally, numerical results show that the proposed channel statistics are consistent with previous results for communication channels. Overall, the proposed model, expressed by the space correlation functions, provides a novel and practical approach to investigate UAV-MIMO channels and design vehicular communication systems.

A General 3-D Non-Stationary 5G Wireless Channel Model

A novel unified framework of geometry-based stochastic models for the fifth generation (5G) wireless communication systems is proposed in this paper. The proposed general 5G channel model aims at capturing small-scale fading channel characteristics of key 5G communication scenarios, such as massive multiple-input multiple-output, high-speed train, vehicle-to-vehicle, and millimeter wave communications. It is a 3-D non-stationary channel model based on the WINNER II and Saleh-Valenzuela channel models considering array-time cluster evolution. Moreover, it can easily be reduced to various simplified channel models by properly adjusting model parameters. Statistical properties of the proposed general 5G small-scale fading channel model are investigated to demonstrate its capability of capturing channel characteristics of various scenarios, with excellent fitting to some corresponding channel measurements.

Deterministic and stochastic simulators for non-isotropic V2V-MIMO wideband channels

In this paper, we consider a novel two-dimensional (2D) geometry-based stochastic model (GBSM) for multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) wideband fading channels. The proposed model employs the combination of a two-ring model and a multiple confocal ellipses model, where the signal is sum of the line-of-sight (LoS) component, single-bounced (SB) rays, and double-bounced (DB) rays. Based on the reference model, we derive some expressions of channel statistical properties, including space-time correlation function (STCF), Doppler spectral power density (DPSD), envelope level crossing rate (LCR) and average fade duration (AFD). In addition, corresponding deterministic and stochastic simulation models are developed based on the reference model. Moreover, we compare the statistical properties of the reference model and the two simulation models in different scenarios and investigate the impact of different vehicular traffic densities (VTDs) on the channel statistical properties of the proposed model. Finally, the great agreement between simulation models and the reference model demonstrates not only the utility of simulation models, but also the correctness of theoretical derivations and simulations.

A geometry-based non-stationary MIMO channel model for vehicular communications

This paper derives a non-stationary multiple-input multiple-output(MIMO) from the one-ring scattering model. The proposed channel model characterizes vehicular radio propagation channels with considerations of moving base and mobile stations, which makes the angle of arrivals (AOAs) along with the angle of departures (AODs) time-variant. We introduce the methodology of including the time-variant impacts when characterizing non-stationary radio propagation channels through the geometrical channel modelling approach. We analyze the statistical properties of the proposed channel model including the local time-variant autocorrelation function (ACF) and the space cross-correlation functions (CCFs). We show that the model developed in this paper for non-stationary scenarios includes the existing one-ring wide-sense stationary channel model as its special case.

A Non-Stationary Geometry-Based Scattering Vehicle-to-Vehicle MIMO Channel Model

In this study, a non-wide-sense stationary geometry-based model that includes both static and mobile scatterers for vehicle-to-vehicle multiple-input multiple-output Ricean fading channels is presented. The proposed channel introduces a two-circle model to describe static vehicles (i.e., around the mobile transmitter (MT) and mobile receiver (MR)) and an ellipse model to depict stationary roadside environments. The relative movement between the MT and MR results in time-variant geometric statistics that make our model non-stationary. Furthermore, the impacts of moving properties of mobile scatterers on the channel statistics are first investigated in the proposed model. Finally, numerical results show that the proposed channel statistics are very close to the prior results, thereby demonstrating the utility of our channel model.

Geometry-Based Model for U-Shaped Strain Gauges on Medical Needles.

The knowledge of needle location during insertions is essential for the success of interventional radiology procedures. As the needle is susceptible to undergo deformations during its insertion into tissues, several methods have been proposed to monitor the needle deformed shape. Thus, instrumented needles with U-shaped strain gauges are currently being developed to reconstruct the shape of the needle from gauge acquisitions. These acquisitions are used in combination with gauge model to obtain estimate of the strain of the needle. The current modeling is limited as it does not consider the geometry of the gauge. This paper introduces a more complete model for U-shaped strain gauge which, unlike the current model, takes into account the width of the gauge. Thus, the impact of width modeling on the strain estimate can be measured and used to improve strain estimation accuracy. Results with real characteristics of instrumented needle devices show that the differences of strain estimate are around few percents. Finally, by taking into account the width and the length of the gauge our model includes the effets of the gauge size on the strain estimation and makes the miniaturization of the gauge less necessary.

A novel 3D GBSM for mmWave MIMO channels

In this paper, a novel three dimensional (3D) wideband geometry-based stochastic model (GBSM) for millimeter wave (mmWave) multiple-input multiple-output (MIMO) channels is proposed. A homogeneous Poisson point process (PPP) is used to generate the clusters in 3D space. The transmitter (Tx) and receiver (Rx) are surrounded by two spheres. The scatterers distributed in the two spheres are introduced to mimic the clustering effects of multipath components (MPCs) in delay and angular domains. The large-scale path loss model and line-of-sight (LOS) probability model are taken into account to make the channel model realistic. In addition, mmWave channel measurements are conducted in an indoor environment. Simulation results based on the two-sphere channel model are compared with measurement results and good agreements are achieved, which validates the proposed channel model. The results indicate that the proposed channel model has good adaptivity and can model the mmWave channel accurately.

A 3-D GBSM Based on Isotropic and Non-Isotropic Scattering for HAP-MIMO Channel

A 3-D geometry-based stochastic model (GBSM) based on two cylinders is proposed for high altitude platform (HAP) communication systems. The proposed 3-D GBSM uses the volume of inner cylinder to model isotropic scattering environment, and that between the inner cylinder and the outer cylinder to model non-isotropic scattering environment. In this letter, the time-variant parameters, including distances between the scatterers and receiver, azimuth angle of departure, and elevation angle of departure (EAOD), are investigated for HAP multiple-input multiple-output (MIMO) channel. The proposed model is validated by the spatial correlation function of measurement results, and the numerical results also demonstrate that the proposed 3-D GBSM with time-varying parameters is applicable to describe the 3-D HAP-MIMO channel.

A Novel 3D Non-Stationary Wireless MIMO Channel Simulator and Hardware Emulator

In this paper, a new WINNER+-based 3-D non-stationary geometry-based stochastic model (GBSM) for multiple-input multiple-output channels is proposed, as well as extended evolving algorithms of time-variant channel parameters. Meanwhile, important statistical properties of the channel model, i.e., time-variant autocorrelation function, time-variant cross-correlation function, and time-variant Doppler power spectrum density are derived and analyzed. Moreover, we propose an efficient hardware implementation method, namely, sum-of-frequency-modulation (SoFM) method, to generate non-stationary channel coefficients. By utilizing compact hardware architecture with SoFM modules, the proposed 3-D non-stationary GBSM is realized on a field-programmable gate array hardware platform. Simulations and hardware measurement results demonstrate that our proposed channel simulator and emulator can get more accurate and realistic Doppler frequency than those of the existing models. In addition, hardware measurements of statistical properties are also well consistent with the corresponding theoretical ones, which verify the correctness of both the hardware emulation scheme and theoretical derivations.

An integrated macroscopic model for simulating SLM and milling processes

Due to their flexibility to also build up highly complex geometries, Additive Manufacturing (AM) processes are increasingly applied. Although near net-shape components can be manufactured using, for example, the Selective Laser Melting (SLM) process, the required surface quality can often not be achieved. In order to manufacture contact areas or functional surfaces, subsequent machining processes can be used to achieve the required accuracy in shape and dimension as well as the desired surface quality. In order to reduce the experimental effort during process design and optimization, simulation systems that are able to efficiently model both processes are required. In this paper, an empirical geometry-based model for SLM and milling processes will be presented. Due to the usage of an empirical model, based on the analysis of a set of reference structures, the simulation of macroscopic geometries can be achieved and used in subsequent milling simulations. Furthermore, an experimental validation of the combination of the two simulation models will be presented.

Comments on "A New Elliptical Model for Device-Free Localization".

A recent paper “A New Elliptical Model for Device-Free Localization” (Sensors 2016, 16, 577) presents a new geometry-based elliptical model for Device-free localization (DFL). In this comment, we point out some problems of the original paper and exploit the same data used in the original paper to demonstrate the existence of these problems. Then, we give a modified formula to correct their model. Meanwhile, a real experiment is performed to verify our conclusion.

Measurements and Analysis of Angular Characteristics and Spatial Correlation for High-Speed Railway Channels

Spatial characteristics of the propagation channel have a vital impact on the application of multi-antenna techniques. This paper analyzes angular characteristics and the spatial correlation for high-speed railway (HSR) channels, based on a novel moving virtual antenna array (MVAA) measurement scheme. The principle of the MVAA scheme is deeply investigated and is further verified by a theoretical geometry-based stochastic model. Using the MVAA scheme, virtual single-input multiple-output (SIMO) channel impulse response data are derived from single-antenna measurements in typical HSR scenarios, involving viaduct, cutting, and station. Based on the SIMO channel data, angle of arrival is extracted according to the unitary estimation of signal parameters by the rotational invariance techniques algorithm, and is compared with the theoretical result. Moreover, power angular spectrum and root mean square (rms) angular spread (AS) are provided, and the rms AS results are statistically modeled and comprehensively compared. In addition, spatial correlation is calculated and analyzed, and a rms AS-dependent spatial correlation model is newly proposed to describe the relationship between the angular dispersion and the spatial correlation. The presented results could be used in multi-antenna channel modeling and will facilitate the assessment of multi-antenna technologies for future HSR mobile communication systems.