Simple Channel Research Articles

A Robust Quantitative Method to Distinguish Runoff‐Generated Debris Flows From Floods

AbstractDebris flows and floods generated by rainfall runoff occur in rocky mountainous landscapes and burned steeplands. Flow type is commonly identified post‐event through interpretation of depositional structures, but these may be poorly preserved or misinterpreted. Prior research indicates that discharge magnitude is commonly amplified in debris flows relative to floods due to volumetric bulking and increased frictional resistance. Here, we use this flow amplification to develop a metric (Q*) to separate debris flows from floods based on the ratio of observed peak discharge to the theoretical maximum water discharge from rainfall runoff. We compile 642 observations of floods and debris flows and demonstrate that Q* distinguishes flow type to ∼92% accuracy. Q* allows for accurate identification of debris flows through simple channel cross‐section surveys rather than through qualitative interpretation of deposits, and therefore should increase the performance of models and engineered structures that require accurate flow‐type observations.

Quantum communications for image transmission over error‐prone channels

AbstractThe introduction of quantum communications, enabled by advancements in quantum computing, is expected to play a significant role in the field of communications. Inherent properties of quantum objects, such as superposition and entanglement, have the potential to provide novel solutions to overcome the challenges encountered by classical communication systems in bandwidth‐intensive applications such as media transmission. This research explores the performance of a quantum communication system in image transmission using quantum superposition and investigates its performance using a simple quantum channel model. With an increase in channel noise, there are significant gains in the rate distortion performance of images transmitted over the quantum channel compared to an ideal classical channel. This novel attempt at constructing a quantum communication‐based image transmission system indicates the potential of the approach to be applied to satisfy the ever‐increasing demands of high‐quality media transmission applications.

Effect of applying serpentine channels and hybrid nanofluid for thermal management of photovoltaic cell: Numerical simulation, ANN and sensitivity analysis

Regarding the importance of thermal management of solar PV cells to achieve higher efficiency and electricity output, a novel configuration by use of serpentine channels for cooling is proposed and numerically investigated in the present article. Moreover, a hybrid nanofluid, (MWCNT)-Fe3O4/water, is employed as the coolant to investigate its potential in further improvement of thermal management. Computational Fluid Dynamics (CFD) is applied to numerically simulate the systems and investigate the impacts of different factors. Performance of the proposed configuration is compared with cooling channels with simple structure without nanofluids. Simulations results revealed that the employment of serpentine channels leads to modification in the thermal management of the cell compared with the simple channel. The maximum improvement rate in this condition compared with simple channels is around 9.63 % that is obtained in case of maximum mass flow rate of coolant and solar radiation intensity. Despite increment in pressure loss by using the serpentine channel compared with the simple channel, 2.6 ×10−3 W and 9.3 ×10−4 W, respectively, in mass flow rate of 0.003 kg/s for water, increase in the generated electricity is much more in this case. Furthermore, numerical results show that applying the hybrid nanofluid with 0.1 % concentration can cause slight reduction in the temperature compared with using water. Moreover, Group Method of Data Handling (GMDH) and Multilayer Perceptron (MLP) neural network as intelligent methods used for estimation of the cell temperature and the maximum error for the developed model is approximately 1.1 % and 0.098 % for the GMDH- and MLP-based models, respectively. Finally, sensitivity analysis is implemented and it is shown that solar radiation intensity is the most influential factor on the cell temperature in condition of using serpentine channels while mass flow rate of the coolant has the minimum relevancy factor and consequently effect on the temperature of the solar cell.

Computational microfluidics of reactive transport processes with solid dissolution and self-induced multiphase flow

There are still many unclear mechanisms in the multiphase reactive flow with solid dissolution processes. In this study, the reactive transport processes coupled with solid dissolution and self-induced multiphase flow in three-dimensional (3D) structures with increasing complexity is studied by developing a 3D computational microfluidic method, which considers multiphase flow, interfacial mass transport, heterogeneous chemical reactions, and solid structure evolution. Solid dissolution diagram in a simple channel in the framework of multiphase flow is proposed, with six coupled multiphase flow and solid dissolution patterns identified and the transition between different patterns discussed. Then, multiphase reactive flow in a porous chip is further studied, and the interesting 3D phenomena are discovered, including enhanced solid dissolution in the middle and enriched bubble generation at the corner along the thickness direction. Considering the importance of reactive surface area, correlations of reactive surface area-porosity-saturation with different dissolution patterns are proposed based on the pore-scale results. Finally, the computational microfluidic model is extended to investigate the multiphase reactive flow in a 3D digital core. Different dissolution patterns are recognized using the local porosity evolution character, and the corresponding pore size distribution and bubble characteristics are deciphered. These findings advance understanding of multiphase reactive transport processes and contribute to improve continuum-scale reactive transport modeling.

Adaptation of Wetland Farming Communities to Modernization: Case Study in Jelapat 1 Village, Indonesia

Modernization can bring progress on the one hand, but on the other hand, modernization may not provide the expected benefits, such as increasing dependence on expensive agricultural inputs and climate change which has an impact on agricultural practices. The main theme of the research is wetland farming communities facing the flow of modernization to outline farming community strategies in adapting wetland farming practices. This research uses a qualitative approach with a case study method based on considering the specificity of the theme according to the characteristics of the research area in Jelapat 1 Village, Tamban District, Barito Kuala Regency. Informants were selected purposively using the criteria of character, membership of farmer groups, and willingness to become informants. Data was collected using observation methods, in-depth interviews, and documentation to obtain valid and varied data. Data were analyzed through data reduction, data presentation, and conclusion drawing stages. For data credibility, triangulation techniques were used. The research results show that farmers in Jelapat 1 Village face water conditions that always inundate agricultural land, which is difficult to control due to strong natural factors. The challenges faced by farmers besides pasang pandit are also dwarf pests and birds. Concerning modernization, it can be concluded that farmers in Jelapat 1 Village use traditional knowledge in adapting agricultural practices in wetlands, namely, arranging planting patterns, making simple water channels, selecting superior seeds that suit wetland criteria, and using organic fertilizer. This phenomenon indicates the conservation of local wisdom in wetland farming in Jelapat 1 Village by the farming community.

Hollow engineering and component optimization strategy to construct flower-like yolk-shell structure SiO2@Void@C@WS2 multicomponent nanocomposites for microwave absorption

Hollow engineering plays a crucial role in enhancing interfacial polarization, which is an essential factor in microwave absorption. Herein, an in-situ growth approach was adopted to successively coating C layer and WS2 nanosheets on the surface SiO2 nanosphere. The obtained results suggested that the formed SiO2@Void@C@WS2 multi-component nanocomposites (MCNCs) reveal a representative flower-like yolk-shell structure, which were manufactured massively through a simple channel. Additionally, the obtained SiO2@Void@C@WS2 MCNCs presented a more and more obvious yolk-shell structure and reduced WS2 content with decreasing the addition of SiO2@C or tungsten and sulfur sources. Because of their distinctive structures and remarkable cooperative effects, the SiO2@Void@C@WS2 displayed excellent microwave absorption performances. Through the majorization of hollow structure and WS2, improved properties of SiO2@Void@C@WS2 MCNCs could be acquired owing to their boosted polarization and conductive loss capabilities. Amongst, the resulting SiO2@Void@C@WS2 MCNCs exhibited the effective absorption band and minimum reflection loss values of 5.40 GHz and −45.50 dB with matching thicknesses of 1.78 and 1.55 mm, respectively. Therefore, our findings employed hollow engineering and optimization strategies for components to design and fabricate the yolk-shell structure flower-like MCNCs, which acted as highly efficient wide-band microwave absorbing materials.

Simplified channel model for indoor VLC systems

The channel model of indoor visible light communication (VLC) is primarily influenced by the receiver’s position and orientation. In this study, we decouple the effects of receiver position and orientation, treating them as independent random variables. This decoupling enables a clearer understanding of how each factor independently influences the channel model. Specifically, we focus on the impact of the azimuth angle, a critical component of orientation, on the VLC channel. We present a simplified channel model for indoor VLC systems based on partial orientation information. Theoretical analysis and simulation results collectively indicate that the accuracy of the simplified channel model is influenced by the field-of-view (FOV), with higher accuracy achieved at narrower FOVs. To evaluate practical performance, we compare our simplified model with the existing complete channel model in a two-user precoding system. Results show that our proposed simplified channel model maintains value, particularly in narrow-FOV scenarios. The research findings indicate that this simplified model is suitable for applications with high demands for channel accuracy in narrow-FOV indoor VLC systems, and can be extended to applications in wide-FOV systems where perfect channel information is not required.

Enhancing performance in solar air channels: A numerical analysis of turbulent flow and heat transfer with novel shaped baffles

Solar air heaters are emerging as a promising solution for sustainable heating, as they harness abundant solar energy to provide heat for a variety of applications. However, their optimum efficiency remains a major challenge. Deflectors have significant potential to improve the performance of solar air heaters by redirecting airflow and optimizing heat transfer, making them more efficient and more suitable for large-scale adoption. This article examines the performance of a new baffle design aimed at improving heat transfer in the channel by increasing the exchange surface between fluid and solid surface. It consists of a “≠” -shaped baffle mounted on the top and bottom walls of the channel. An in-depth analysis of the spacing between these baffles was carried out to assess their impact on the thermal and aerodynamic properties of the solar air channel. Computational Fluid Dynamics (CFD) was used to perform the calculations, using the Finite Volume Method (FVM) in conjunction with the SIMPLE algorithm. All studies are carried out using the CFD code Fluent. Crucial steps in this research include studying the influence of these new baffles at different Reynolds numbers, ranging from 15000 to 35000, as well as varying the separation distance between the two baffles, chosen periodically (DBaffle/2, 3DBaffle/4, DBaffle, 5DBaffle/4 and 3DBaffle/2). Some of the numerical results were validated with the available experimental data and showed satisfactory agreement. The study identified an optimal case for the new baffles, by reducing the distance between the baffles, an improvement in system performance was observed, by increasing the flow strength and widening the recycling cells, which has an impact on dynamic behavior and heat transfer. The presence of this new baffle design, with minimal separation distance between them, demonstrated a significant thermal improvement, with a thermal improvement factor increasing by 44% compared to the simple channel without baffles, thus highlighting the effectiveness of the new solar air channel with “≠” -shaped baffles.

A pressure-projection pre-conditioning multi-fractional-step method for Navier–Stokes Flow in Porous Media

A new pressure-projection pre-conditioning multi-fractional-step (PPP-MFS) method for incompressible Navier–Stokes flow in porous media is presented. This fractional step method is applied to decouple the pressure and the velocity; thereby, overcoming the computational costs and difficulty associated with the resolution of the nonlinear term in the Navier–Stokes equation for fine geometric models. Specifically, time evolution is decomposed into a sequence of multi-fractional solution steps. In the first step, an elliptic problem is solved for pressure (p) with a no-slip boundary condition. This gives the Stokes pressure and velocity fields. In the second step, the obtained pressure p is then projected onto the field p∗ and used to solve for velocity field (u) required for the pre-conditioning of the solution to the Navier–Stokes equation. The pressure and velocity fields are obtained from the solution of the Navier–Stokes equation in the third step. Numerical and geometric discretisation of porous samples were carried out using finite-element method. For flow in simple channel models represented by two- and three-dimensions and in systems with high conductivity, the Stokes and Navier–Stokes numerical solutions produced close pressure and velocity field approximations. For flow around a cylinder, computation time is consistently higher in the Navier–Stokes equation by a factor of 2 with a pronounced non-symmetric pressure field at high mesh refinements. This computation time is desirable given that Navier–Stokes computation without preconditioning can be orders of magnitude more expensive.

Polar code-based secure transmission with higher message rate combining channel entropy and computational entropy

The existing physical layer security schemes, which are based on the key generation model and the wire-tap channel model, achieve security by utilizing channel reciprocity entropy and noise entropy, respectively. In contrast, we propose a novel secure transmission framework that combines noise entropy with reciprocity entropy, achieved by inserting reciprocity entropy into the frozen bits of polar codes. Note that in real-world scenarios, when eavesdroppers employ polynomial-time attacks, the bit error rate (BER) increases due to the introduction of computational entropy. To achieve indistinguishability security, we convert the practical physical layer security metric, BER, into the average min-entropy, a widely accepted concept in cryptography. The simulation results demonstrate that the eavesdropper’s BER can be significantly increased without compromising the communication performance of the legitimate receiver. Under concrete parameters we selected, when compared to the joint scheme of physical layer key generation and one time pad, the modular semantically-secure scheme based on the wire-tap channel model, and the simple channel entropy combination scheme, our scheme achieves a message rate approximately 1.2 times, 3.8 times, and 1.4 times better, respectively. Experimental testing validates the feasibility of our scheme.

The Impact of a Simple Channel Factor on Vocabulary Learning of Iranian EFL Learners Across Genders

The concept of channel factors was introduced by Kurt Lewin to the field of psychology as seemingly unimportant circumstantial changes that could affect the trajectory of an endeavor. The primary goal of the present study was the examination of the impact of using a timeslot on Iranian English as a Foreign Language (EFL) learners' performance on vocabulary, and the respective comparison based on gender. A total number of 180 male and female upper-intermediate EFL learners participated in this study. They were divided into six classes: two classes were not provided with the channel factor, two of them received it from the outset, and the other two were exposed to it in the middle of the semester. The participants, all of whom took three tests (pretest, mid-test, post-test), were categorized into six types based on their gender and the existence and timing of the channel factors. The results of data analysis through Analysis of Variance (ANOVA) revealed that the channel factor positively impacted the performance of participants regardless of gender. However, its impact was stronger on males in the short run but more endurable among females.

Slump-flow channel test for evaluating the relations between spreading and rheological parameters of sediment mixtures

Understanding debris flow phenomena and modeling them effectively requires accurate estimation of their rheological parameters. This study introduces a simple approach defined as the “slump-flow channel test”, which employs a horizontal rectangular channel to evaluate these parameters. The results of slump-flow channel tests indicate that the spreading parameters (spread length, angle of reach, and time to final spread) of sediment mixtures are strongly influenced by their sediment fractions and rheological properties. An empirical analysis of the temporal evolution of the spread length and spread velocity was carried out employing both experimental and simulation results. The numerical simulation of the slump-flow channel tests was performed using the Flow-3D software. Both experimental and simulation results demonstrate that the spreading and the rheological parameters of sediment mixtures exhibit strong correlations and this implies that the rheological parameters of sediment mixtures can be evaluated indirectly using a simple slump-flow channel test.

A Novel DC Electroosmotic Micromixer Based on Helical Vortices

This work introduces a novel direct current electroosmosis (DCEO) micromixer designed for rapid and efficient fluid mixing. This micromixer demonstrates excellent capability, achieving approximately 98.5% mixing efficiency within a one-second timespan and 99.8% efficiency within two seconds, all within a simple channel of only 1000 µm in length. A distinctive feature of this micromixer is its ability to generate robust and stable helical vortices by applying a controlled DC electric field. Unlike complex, intricate microfluidic designs, this work proposes a simple yet effective approach to fluid mixing, making it a versatile tool suitable for various applications. In addition, through simple modifications to the driving signal configuration and channel geometry, the mixing efficiency can be further enhanced to 99.3% in one second.

Reduction of the received signal strength variation with distance using averaging over multiple heights and frequencies

As a simple and inexpensive channel characteristic, received signal strength (RSS) finds extensive usage in localization applications. However, the quick changes in signal strength impact the localization precision. By averaging over access points (APs) with multiple frequencies and/or heights, this article suggests a novel approach to lowering RSS fluctuation. Initially focused on the plane-earth loss model, the study was later extended to include a multipath indoor propagation scenario that was simulated. We used ray-tracing software to model the indoor propagation situation. This research takes into account the results of three distinct methods for averaging RSS: height averaging, frequency averaging, and hybrid frequency and height (FH) averaging, which combines the two. We discovered that the Height-only strategy considerably decreased the RSS variation with distance for both settings we looked at. Using the frequency-only method even further reduced the variation. Using the Hybrid FH technique greatly enhances the results. Root mean square error values of 4.427 dB, 3.70 dB, and 3.5 dB, respectively, are provided for the averaging approaches and the ideal scenario in which no variance occurs. Another finding is that averaging with APs that have double the height or frequency will not improve the RSS distance variation.

The influence of magneto-hydrodynamics and vortex generators on nanofluids heat transfer

This paper investigates the effects of a vortex generator (VG) and magneto-hydrodynamics (MHD) on the thermal properties of nanofluids in a microchannel. A variety of test scenarios within the laminar flow regimes are numerically examined: nanofluids in a hot-walled simple channel (SC); nanofluids in a heated-walled channel where a circular cylinder is embedded within the channel and functions as a vortex generator (VG); nanofluids in a heated-walled channel that incorporates both a vortex generator and magneto-hydrodynamics (VG-MHD). The channel has a circular cylinder with a diameter of D that is fixed inside the channel with various gap ratios (GR = G/D) ranging from 0.5 to 4.0. Numerical investigations for laminar flow with Re ≤ 1,000 are carried out. The nanoparticle volume fractions range from 0 % to 7 %, and the magnetic field is set at 0.05 T. The best heat transmission conditions with the lowest skin friction coefficient are evaluated for the optimal GR. It is found that heat transfer is enhanced by approximately 20 % when MHD and VG effects are employed, in contrast to a traditional channel that does not utilize the MHD effect.

Modeling of hydrogen flow decompression from a storage by a two-stage Tesla valve: A hybrid approach of artificial neural network, response surface methodology, and genetic algorithm optimization

Hydrogen, as an energy carrier, requires efficient handling and regulation, especially during storage and release phases. The efficient hydrogen release from the storage tanks is often coupled with a rapid decompression process. Pressure regulators, hydrogen sensors, and monitoring systems are commonly used to control the pressure of hydrogen gas in storage tanks and distribution systems. Besides the mentioned methods, Tesla valves offer a compelling solution due to their unique design and functionality. In the current research, a novel two-stage Tesla valve was designed to regulate the hydrogen flow in both forward and reverse directions. Artificial neural networks (ANN) and response surface methodology (RSM) were applied to provide the prediction models. Presenting these ready-made and pre-determined models can help researchers and developers of Tesla valves to achieve their goals in the shortest time and with the lowest cost. In this research, two different prediction models were employed to predict the diodicity (Di) and absolute pressure drop ratio (APDR) in the Tesla valve. The distance between stages (X), length of divider (L), valve angle (θ), and depth of divider penetration (H) are the input variables of the prediction models. These variables, as the most influential parameters, are carefully selected and manipulated within specified ranges. Moreover, single- and multi-objective optimizations were performed by genetic algorithm, and the Pareto fronts for Di and APDR were presented. For the first time, the combination of these three methods (ANN, RSM, and genetic algorithm) was employed herein to investigate the decompression performance and hydraulic behavior of Tesla valves. Based on the findings, the ANN models exhibited higher accuracy with R2 values of 0.991 relative to RSM models (for both responses). The optimized design significantly enhanced the pressure drop of hydrogen flow in the reverse direction, resulting in an improvement of about 379.5 % in diodicity. Besides, the novel two-staged Tesla valve enhanced the pressure drop by about 4830 % and 1354 % in reverse and forward directions compared to the simple straight channel.

Equalizer Parameters’ Adjustment Based on an Oversampled Channel Model for OFDM Modulation Systems

A physical model of a wireless transmission channel in the time domain usually consists of the main propagation path and only a few reflections. The reasonable assumptions made about the channel model can improve its parameters’ estimation by a greedy OFDM (Orthogonal Frequency Division Multiplexing) equalizer. The equalizer works flawlessly if delays between propagation paths are in the sampling grid. Otherwise, the channel impulse response loses its compressible characteristic and the number of coefficients to find increases. It is possible to get back to the simple channel model by data oversampling. The paper describes how the above idea helps the OMP (Orthogonal Matching Pursuit) algorithm estimate channel coefficients. The authors analyze the oversampling algorithm on the one hand to assess the influence of filtering function and signal resolution on the quality of the channel impulse response reconstruction. On the other hand, the abilities of the OMP algorithm are analyzed to distinguish components of the oversampled signal. Based on these analyses, we proposed modifications to the compressible channel’s impulse response reconstruction algorithm to minimize the number of transmission errors. A distinction was made between the filters used in the OMP search and channel reconstruction stages before calculating equalizer coefficients. Additionally, the results of the search stage were considered as elements within the groups.

An Information-Theoretic Approach to Joint Sensing and Communication

A communication setup is considered where a single transmitter wishes to convey messages to one or two receivers and simultaneously estimate the states of the receivers through the backscattered signals of the emitted waveform. The scenario at hand is motivated by joint radar and communication, which aims to co-design radar sensing and communication over shared spectrum and hardware. In this paper, we model the communication channel as a simple memoryless channel with independent and identically distributed (i.i.d.) time-varying state sequences and we model the backscattered signals by (strictly causal) generalized feedback. For single-receiver systems of this form, we fully characterize the capacity-distortion tradeoff, defined as the largest rate at which a message can reliably be conveyed to the receiver while simultaneously allowing the transmitter to sense the state sequence with a given allowed distortion. Our results show a tradeoff between the achievable rates and distortions, and that this tradeoff only stems from a common choice of the input distribution (the waveform) but not from other properties of the utilized codes. To better illustrate the capacity-distortion tradeoff, we propose a numerical method to compute the optimal inputs (waveforms) that achieve the desired tradeoff. For two-receiver systems with two states, we characterize the capacity-distortion tradeoff region of physically degraded broadcast channels (BC) as a rather straightforward extension of the single receiver case. Here, a tradeoff not only arises between sensing and communication performances but also between the various rates and the distortions of the different states. Similarly to the single-receiver case, the optimal co-design scheme exploits the generalized feedback signals only for sensing but not for improving communication performance. This is different for general two-receiver BCs, where optimal co-design schemes exploit generalized feedback also to improve capacity. However, as we show, also for BCs the optimal sensing performance only depends on the chosen input distribution (waveform) but not on the code construction used to accomplish the communication task. For general BCs, we provide inner and outer bounds on the capacity-distortion region, as well as a sufficient condition when this capacity-distortion region is equal to the product of the capacity region and the set of achievable distortions, in which case no tradeoff between sensing and communication occurs. A number of illustrative examples demonstrate that the optimal co-design schemes outperform conventional schemes that split the resources between sensing and communication, both for single-receiver and BC systems.

Performance boost of an integrated photovoltaic-thermal and solar thermal collectors using minichannel heat sink: Energy, exergy, and environmental analysis

This case study investigates the enhancement of thermo-electric efficiency of an integrated photovoltaic-thermal and solar thermal collectors through the utilization of a minichannel heat sink. The integration of a photovoltaic-thermal collector and a solar thermal collector forms a cohesive system designed to minimize heat loss and streamline the external connection process. The energy, exergy, and environmental analysis of the integrated system are numerically investigated and compared by four solar systems including a photovoltaic module, solar thermal collector, photovoltaic-thermal collector, and simple channel-based integrated system. The results of energy analysis show that among the five investigated systems, the maximum electrical and thermal power is obtained using minichannel-based integrated systems, which are 0.8 % and 55.8 % higher than those of photovoltaic-thermal systems, respectively. By using minichannels instead of the simple channel, the electrical and thermal exergy of the integrated system increases by 0.80 % and 7.16 %, respectively. The greater effect of the solar radiation on the systems’ performance than other operating parameters is found from the results so the total power of the minichannel-based integrated systems increases by 245.39 W, by increasing the radiation rate from 700 W/m2 to 1100 W/m2. The annual CO2 mitigation of the integrated system, in term of energy, is 11.54 tCO2/annum, which is 81.5 % and 56.8 % more than photovoltaic module and solar thermal collector, respectively.

Machine learning for rapid discovery of laminar flow channel wall modifications that enhance heat transfer

Numerical simulation of fluid flow plays an essential role in modeling many physical phenomena, which enables technological advancements, contributes to sustainable practices, and expands our understanding of various natural and engineered systems. The calculation of heat transfer in fluid flow in simple flat channels is a relatively easy task for various simulation methods. However, once the channel geometry becomes more complex, numerical simulations become a bottleneck in optimizing wall geometries. We present a combination of accurate numerical simulations of arbitrary, flat, and non-flat channels as well as machine learning models trained on simulated data to predict the drag coefficient and Stanton number. We show that convolutional neural networks (CNNs) can accurately predict target properties at a fraction of the computational cost of numerical simulations. We use CNN models in a virtual high-throughput screening approach to explore a large number of possible, randomly generated wall architectures. Data augmentation techniques are incorporated to enforce physical invariances toward shifting and flipping, contributing to precise prediction for fluid flow and heat transfer characteristics. Moreover, we approach the interpretation of the trained model to better understand relevant channel structures and their influence on heat transfer. The general approach is not only applicable to simple flow setups as presented here but can be extended to more complex tasks, such as multiphase or even reactive unit operations in chemical engineering.