Device Model Research Articles

Current–Pressure Dynamics Modeling on an Annular Magnetorheological Valve for an Adaptive Rehabilitation Device for Disabled Individuals

The dynamic relationship between current and pressure in magnetorheological (MR) valves is essential for the design of adaptive rehabilitation devices aimed at health rehabilitation for disabled individuals, yet it remains under-explored in existing modeling approaches. Accurately capturing this relationship is vital to predict the pressure drop response to current variations, facilitating the development of effective control systems in such rehabilitation applications. This study employs a linear black-box modeling approach to characterize the current–pressure dynamics of an annular MR valve. Experimental data are used to develop a set of transfer function models, with parameters identified through MATLAB’s system identification tools, utilizing invariant variable regression and the Levenberg–Marquardt (LM) iteration. The modeling yielded a 14th-order transfer function, labeled TF14, which closely aligns with experimental data, achieving a root mean square error of 12.64%. These findings contribute valuable insights into the current–pressure dynamics of MR valves and establish a foundational model for adaptive rehabilitation devices designed for individuals with disabilities.

Research and Mechanism Design Analysis of Leg Lifting Device Based on Human Body Stretching

Leg stretching devices are one of the main instruments used to improve human function. To solve the limitations of existing leg stretching products, such as single function and low degree of coincidence, a leg stretching device satisfying ergonomics was studied in this paper. Firstly, the Box–Behnken Design (BBD) response surface methodology was applied to establish a regression model for leg force. Secondly, a motion analysis was conducted on the leg lifting mechanism using analytical methods, and the model data were coupled by Creo Parametric and Automatic Dynamic Analysis of Mechanical System (ADAMS) 2019 software to develop the kinematic model. Then, the motion characteristics during the whole process were studied, and the motion parameter curves were obtained. Next, ABAQUS 2022 software was employed to create the finite element simulation model of the leg lifting device, and key component strength was also analyzed. Finally, a prototype of the device was made and experimentally validated with leg lifting. The results show that in the case of different heights and weights, the lifting angle of the human leg has a significant effect on the force state during the leg lifting process. When the leg is lifted 0–30°, the force on the leg is small. As the leg lifting angle increases, the force on the leg also increases. In the process of leg lifting, the angular velocity and angular acceleration of the leg lifting mechanism change more gently, and there is no obvious mutation. The maximum stress of the driving rod is 102.5 MPa, the maximum stress of the lifting rod is 88.12 MPa, and the maximum stress of the leg placing plate is 40.5 MPa, all of which meet the strength requirements and provide a reference for the research of the human leg stretching device.

Analysis of errors in junction temperature estimated by temperature-sensitive electrical parameter for parallel-connected SBDs

Abstract Multi-chip topology is widely adopted for large rated current power modules. Thermal management of multi-chip power modules has a significant impact on their long-term reliability. The transient thermal network model used for thermal management relies on the time response of junction temperature, which is estimated using temperature-sensitive electrical parameters (TSEPs) derived from the temperature dependency of I-V characteristics in power devices. However, the parallel connection of power devices complicates the junction temperature estimation because the sensing current is shared unevenly due to differences in the I-V characteristics of individual devices and the temperature gradient within the power module package. Consequently, the temperature estimated using a unified TSEP does not accurately represent the temperature difference among parallel-connected power devices. This paper investigates an error in the junction temperature estimated by using unified static TSEP for parallel-connected silicon carbide (SiC) Schottky barrier diodes (SBDs) as the power device. The results reveal that the unified TSEP underestimates the maximum temperature in multi-chip power modules. However, the semi-physical model of power devices enables us to estimate the junction temperature of each SiC SBD when we measure shared currents for each device.

Simulation Analysis of an ETC Monitoring and Imaging Supplementary Lighting Device for Freeways

To address the glare issues caused by highway ETC gantry monitoring and imaging illumination devices, this paper first investigates the mechanism of disability glare and derives the formula for the glare threshold increment. Subsequently, using the glare increment threshold as the evaluation metric and incorporating the current regulatory requirements for illumination devices, a simulation model for ETC gantry monitoring and imaging illumination devices was developed. A single-variable control method was applied to conduct simulation experiments on the glare problems from multiple perspectives (e.g., different standard illuminance levels, various luminous areas, varying installation heights, and different lateral offsets), and the glare level was analyzed using the glare increment threshold method. It was found that when the lateral offset of the illumination device reached 4 m, the glare increment threshold decreased by more than 50%. Additionally, it is recommended that the illuminance of the illumination device should be greater than 15 lx.

Enhanced energy storage in relaxor (1-x)Bi0.5Na0.5TiO3-xBaZryTi1-yO3 thin films by morphotropic phase boundary engineering

Perovskites at the crossover between ferroelectric and relaxor are often used to realize dielectric capacitors with high energy and power density and simultaneously good efficiency. Lead-free Bi0.5Na0.5TiO3 is gaining importance in showing an alternative to lead-based devices. Here we show that (1-x)Bi0.5Na0.5TiO3 – xBaZryTi1-yO3 (best: 0.94Bi0.5Na0.5TiO3 -0.06BaZr0.4Ti0.6O3) shows an increase of recoverable energy density and electric breakdown upon chemical substitution. In thin films derived from Chemical Solution Deposition, we observed that polarization peaks at the morphotropic phase boundary at x = 0.06. While Zr substitution results in reduced polarization, it enhances both efficiency and electric breakdown strength, ultimately doubling the recoverable energy density and the metallization interface by lowering surface roughness. Our dielectric capacitor shows <3% deviation of energy properties over 106 cycles. A virtual device model of a multilayer thin film capacitor (7.25 mJ recoverable energy) was used to compare its performance to already in use multilayer ceramic capacitors.

Study of the effect of circular p-GaN gate on the DC characteristics of AlGaN/GaN HEMTs

Abstract In this paper, we use Silvaco-ATLAS two-dimensional numerical simulation to calculate the performance of two different circular-gate AlGaN/GaN HEMT device models. The influence of the special circular-gate structure on the DC characteristics of the AlGaN/GaN HEMT device is studied and compared with that of conventional devices. Compared with conventional, the threshold voltage of the drain-center and source-center circular-gate devices increased from 1.1 V to 1.5 V, while the transconductance improved from 245 mS/mm to 328 mS/mm and 285 mS/mm respectively. In the on-state of devices, the maximum saturation output current increased from 536 mA/mm to 620 mA/mm and 650 mA/mm. Furthermore, the breakdown voltage of the source-center circular-gate device rose from 765 V to 870 V compared to conventional devices; however, for the drain-center circular-gate device it was only at 685 V due to concentrated electric fields outside the drain region—this limitation can be effectively addressed by increasing the drain area. Simulation results demonstrate that circular-gate AlGaN/GaN HEMT devices can avoid edge effects, improve electric field distribution, and alleviate self-heating effects.&amp;#xD;

Precision and Accuracy Analysis of PM2.5 Light-Scattering Sensor: Field and Laboratory Experiments

The widely used low-cost particulate matter (PM) sensors in Thailand, such as the DustBoy, require performance improvements to ensure their data align with the established standards set by the US Environmental Protection Agency (US EPA). This study evaluates the accuracy and reliability of the DustBoy, a commonly used PM2.5 monitoring device in Thailand. A comparative analysis was conducted between the DustBoy and the US EPA’s Federal Reference Method (FRM) and Federal Equivalent Method (FEM). The research involved both laboratory and field testing, where the DustBoy’s performance was analyzed at various particulate matter concentration levels and environmental conditions. The study demonstrated that the DustBoy readings diverged from those of standard monitors at higher PM2.5 concentrations; however, a positive correlation between the devices remained evident. Below 100 µg/m3, the DustBoy overestimated PM concentrations compared to the FRM devices but underestimated them compared to the FEM devices. At higher concentrations, the DustBoy showed a significant overestimation, although the data trends aligned with those of standard devices. The sensor performance was also affected by factors such as the sensor age and device model. Corrections were developed to adjust the DustBoy readings to match the reference devices more closely, enhancing the accuracy post-adjustment. These corrections will refine the DustBoy’s public data reporting and serve as guidelines for other low-cost sensors in Thailand.

Device modelling and performance enhancement of FASnI3-based perovskite solar cell with diverse, compatible charge transport layers

Device modelling and performance enhancement of FASnI3-based perovskite solar cell with diverse, compatible charge transport layers

Building energy management model integrating rule-based control algorithm and genetic algorithm

Energy is a crucial material foundation for the development of human society. Building energy consumption accounts for a significant proportion of global energy consumption. Optimizing building energy management is of great significance for achieving sustainable development. A building energy management model that integrates rule-based control algorithm and genetic algorithm is proposed, aiming to optimize building energy utilization and reduce operating costs. Mathematical models for different devices in the building energy system are established, and the rule-based control algorithm is used to provide system decision support. Then, the genetic algorithm is integrated to address the complexity and uncertainty of energy optimization problems. The comparative test results showed that the proposed fusion algorithm had higher fitness values and faster convergence speed. The root mean square errors of the algorithm in the training and testing sets were 43.6544 and 43.6844, with the lowest error and highest accuracy among the four algorithms. The simulation experiment results showed that the building energy management model integrating rule-based control algorithm and genetic algorithm had energy expenditures of 788.3 yuan and 967.6 yuan for two types of buildings, respectively. Taking Building 1 as an example, compared with Supervisory Control and Data Acquisition (SCADA), Beetle Antennae Search and Particle Swarm Optimization (BAS-PSO) algorithm, and Long Short-Term Memory-Convolutional Neural Network (LSTM-CNN) algorithm, the proposed model reduced the cost of energy consumption optimization by 39.30%, 28.32%, and 20.20%, respectively. Overall, the proposed building energy management model effectively reduces operating costs, utilizes building energy, and contributes to daily building energy management and decision support.

Physics-Informed Machine Learning for the Efficient Modeling of High-Frequency Devices

Physics-Informed Machine Learning for the Efficient Modeling of High-Frequency Devices

Advanced measurement methods for high-power gallium nitride high electron mobility transistors.

The testing and modeling of semiconductor devices are the foundation of circuit design. The issue of high-power device testing urgently needs to be solved as the power level of the devices under test (DUTs) increases. This work proposes advanced measurement methods based on three aspects of "measuring capability, security, and stability" with a focus on the features of high output power, easy self-oscillation in mismatch tests, and safety risk in the measurement system of high-power transistors. In this paper, the wideband limiter and bias filter network are innovatively introduced to improve the stability and security of the measurement circuit. Meanwhile, the output signal of the DUT is suggested to be measured using a spectrum analyzer before the test to avoid damage to the circuit caused by the possible self-oscillation of the transistor. Moreover, an efficient test system of current parameters and S-parameters is developed, with coaxial fixtures offered to boost the test power capacity and cascade bridges adapted to satisfy the pulse operating conditions. Finally, based on the improved test methods, a gallium nitride high electron mobility transistor (GaN HEMT) with a gate width of 400 × 32μm and a power density of roughly 10 W/mm was tested. A relatively complete I-V curve and a S-parameter curve were obtained, demonstrating the effectiveness and applicability of the improved methods.

An intimal-lumen model in a microfluidic device: potential platform for atherosclerosis-related studies.

Atherosclerosis is a chronic inflammatory vascular disorder driven by factors such as endothelial dysfunction, hypertension, hyperlipidemia, and arterial calcification, and is considered a leading global cause of death. Existing atherosclerosis models have limitations due to the absence of an appropriate hemodynamic microenvironment in vitro and interspecies differences in vivo. Here, we develop a simple but robust microfluidic intimal-lumen model of early atherosclerosis using interconnected dual channels for studying monocyte transmigration and foam cell formation at an arterial shear rate. To the best of our knowledge, this is the first study that creates a physiologically relevant microenvironment under an arterial shear rate to modulate lipid-laden foam cells on a microfluidic platform. As a proof of concept, we use murine endothelial cells to develop a vascular lumen in one channel and collagen-embedded murine smooth muscle cells to mimic the subendothelial intimal layer in another channel. The model successfully triggers endothelial dysfunction upon TNF-α stimulation, initiating monocyte adhesion to the endothelial monolayer under the arterial shear rate. Unlike existing in vitro models, native low-density lipoprotein (LDL) is added in the culture media instead of ox-LDL to stimulate subendothelial lipid accumulation, thereby mimicking more accurate physiology. The subendothelial transmigration of adherent monocytes and subsequent foam cell formation is also achieved under flow conditions in the model. The model also investigates the inhibitory effect of aspirin in monocyte adhesion and transmigration. The model exhibits a significant dose-dependent reduction in monocyte adhesion and transmigration upon aspirin treatment, making it an excellent tool for drug testing.

Multi‐time‐scale scheduling of integrated port logistics‐energy system considering piecewise linearization of high‐order equations

AbstractPort area usually possesses a high percentage of fluctuating energy sources (wind turbine and photovoltaic systems and fluctuating load. How to rationally dispatch port resources and arrange equipment operation plan is crucial in the development of environmentally‐friendly ports. Producing hydrogen using renewable energy sources is an important technical method to promote the utilization of renewable energy. In order to balance the high electricity consumption and unstable output of renewable energy sources, previous studies have proposed a scheduling model for the port logistics‐energy integrated system. However, inaccurate modelling of hydrogen storage devices has impacted the security of system operation. Considering the temperature and pressure of hydrogen in the high‐pressure hydrogen storage tank, this paper established the multi‐time scale scheduling model of the port logistics‐energy integrated system. The excessive electrical energy is stored using electrolytic water hydrogen production technology. On this basis, the electricity and hydrogen load demands are coordinated. Then, a piecewise‐linearization method is proposed to efficiently solve the high‐order nonlinearity temperature‐pressure equation. Finally, the feasibility and accuracy of the proposed method is verified by testing on a standard port integrated energy system.

Modeling of Tunable Electronic Waveguide Devices in Graphene Using Conservative Higher Order Time Stepping

Modeling of Tunable Electronic Waveguide Devices in Graphene Using Conservative Higher Order Time Stepping

Analyzing the Vulnerability of Consumer IoT Devices to Sophisticated Phishing Attacks and Ransomware Threats in Home Automation Systems

This research presents a new and elaborate security model for IoT devices used in home automation systems. The framework comprises five algorithms: The following models were identified: Vulnerability Assessment (VA), Anomaly Detection with Machine Learning (ADML), Behavior Analysis (BA), Intrusion Detection System (IDS), and Adaptive Security Framework (ASF). Ablation study brings out the specificity of each algorithm and underlines the synergy of the algorithms for IoT device protection. Comparisons with similar procedures confirm higher levels of sensitivity and specificity of the proposed method, as well as enhanced efficiency and tunability. Animated charts give crisp information about the total effects of security methods on different parameters. The proposed security framework has therefore been presented as now a viable solution to complex threats and continuous security for the IoT devices used in home automation systems.

DualRec: A Collaborative Training Framework for Device and Cloud Recommendation Models

DualRec: A Collaborative Training Framework for Device and Cloud Recommendation Models

DFT+NEGF Insights on Boosting the Thermoelectric Figure of Merit of 2D GeTe/arsenene vdW Heterostructure Device: Interface Engineering

Stacking two-dimensional materials into van der Waal heterostructures (vdWH) is a promising choice for thermoelectric devices. Applying the first-principles method with NEGF formalism, we examined the structural, electronic study, and thermoelectrical transport features of the GeTe/arsenene 2D vdW heterostructure and its constituent monolayer. Heterostructures are constructed by combining GeTe with arsenene (AS) monolayers through vdW stacking using the Coincident site lattice (CSL) theory. The stability of these vdWH is proven by the parameters of interlayer distances, binding energies, and dynamical stability. The stable heterostructure exhibits an indirect bandgap (0.41 eV) with a band-type-II profile. A two-probe device model of the armchair (AC_vdWH) and zigzag (ZZ_vdWH) oriented systems are constructed to examine the thermoelectric transport properties. The thermoelectric transport properties are discussed in terms of different temperatures and chemical potentials. The negative Seebeck coefficient of the systems depicts an n-type character. Thermoelectric studies indicate that the AC_vdWH improves performance due to a reduction in phonon transmittance (26.83 nW/K) and a high Seebeck coefficient (-384.7 μV/K) at room temperature. Our findings predict that n-type AC_GeTe/arsenene vdWH with a high ZT value of 4.4 at 400 K, will be the promising choice for low-temperature thermoelectric device applications.

Ferroelectrically gated sub-6 nm monolayer MoS2 transistors for high-performance and low-power applications

A schematic device model and the corresponding transfer characteristics with upward (P↑) and downward (P↓) polarizations of BiAlO3 at Vb = 0.64 V are presented.

Charged Device Model ESD Sensitivity Tester Design and Application

Charged Device Model ESD Sensitivity Tester Design and Application

Inflow Control Device with Electro-Hydraulic Control System

This article presents an in-depth exploration of the design, modeling, and control of an advanced inflow control device (ICD). Existing control systems for ICDs are analyzed, highlighting their key features and assessing their advantages and drawbacks. Based on this analysis, the development of a new ICD design is proposed incorporating an electro-hydraulic control system. The mathematical description of the valve operation is provided, elucidating the principles behind its functioning. To simulate and evaluate the performance of the proposed ICD, a comprehensive model is built using Simulink, integrating a matrix approach and neural networks. The model enables the qualitative determination of the valve position based on the generated pressure drop, contributing to the optimization of the device’s performance. The article emphasizes the importance of automatically adjusting the actuator’s position based on real-time measurements from various instruments. This enhances the efficiency and reliability of the ICD in dynamically controlling the flow rate in production wells. The use of a neural network-based approach aids in accurately determining the density of the flowing fluid and its impact on pressure drop, facilitating effective control strategies. The results of their research are demonstrated, showcasing the successful operation of the developed ICD model. Through the use of 3D views and crosssectional diagrams, the article provides a visual understanding of the ICD’s components, including the overall device, central axis, and pressure sensor setting. This article contributes to the advancement of inflow control devices by offering novel insights into their design, mathematical modeling, and control mechanisms. The findings pave the way for improved reservoir management, enhanced production optimization, and more efficient utilization of oil and gas resources.