Search Results (17)

A precise high-order segmented curvature-compensation bandgap reference (BGR) with dynamic element matching (DEM) offset cancellation has been developed. The proposed segmented curvature-compensation scheme with a resistive trimming network is used to reduce the errors caused by the nonlinear dependence of the bipolar transistor base-emitter voltage ($V_{\mathit{BE}}$) on temperature. To decrease the std dev ($\sigma$) of the reference voltage ($V_{\mathit{REF}}$), DEM technology is applied in the core BGR to alleviate the current branch mismatch, as well as the current mirror mismatch in the error amplifier. The proposed BGR circuit is designed on a 0.18 $\mathsf{\mu }$m BCD process with an active area of $300\times 375$$\mathsf{\mu }$m and 61.5 $\mathsf{\mu }$A@5 V current consumption in the bandgap core circuit. The post-simulation results show that the proposed BGR achieves a temperature coefficient (TC) of 0.81–1.46 ppm/°C from −40 °C to 125 °C and a 0.045% $\sigma$/$\mu$ variation on a 3.2768 V $V_{\mathit{REF}}$. Full article

This study investigates the morphological evolution of river particles and their mechanical behavior during sediment transport. River particles exhibit distinct shape differences between upstream and downstream sections, with particles becoming progressively rounded downstream. The rounding process is quantitatively described using morphological indices. The analysis reveals upstream particles are more angular, while downstream particles become increasingly rounded due to erosion and abrasion, modeled by a unified abrasion function. The Loop subdivision method effectively simulates this gradual rounding process. Additionally, the Discrete Element Method (DEM) calculates the natural angle of repose for particles with varying erosion levels, showing angles ranging from 38.2° for angular particles to 34.4° for rounded particles, closely matching field observations. The numerical results effectively demonstrate the interlocking effect caused by particle morphology. This research enhances the understanding of sediment transport dynamics and provides a robust framework for modeling particle shape evolution. Full article

In order to precisely reproduce the precise seeding process of the population in the air-suction seed-metering device, it is necessary to execute accurate modeling of seed particles using the bonded-particle model, in combination with the discrete element method (DEM) and computational fluid dynamics (CFD). Through the repose angle, slope screening, rotating container, and particle sedimentation experiments, in this paper, the influence of the filling accuracy of the bonded-particle model on the flow behavior and mixing characteristics of the seed population was first explored based on EDEM software. The viability of the suggested modeling approach for pelleted vegetable seeds, as described in this study, was confirmed by comparing experimental and simulation outcomes. The surface roughness values obtained from the studies above were utilized to assess the accuracy of the bonded-particle model in filling. Additionally, a mathematical technique for determining the surface roughness was provided. Furthermore, an analysis of the multiple contacts in the bonded-particle model was also performed. The results indicated that the simulation results closely matched the experimental data when the number of sub-spheres in the bonded-particle model was equal to or more than 70, as measured by the standard deviation. In addition, the most optimal modeling scheme for the pelletized vegetable seed bonded-particles, based on the cost of coupling simulation, was found to be the bonded-particle surface roughness (BS) with a value of 0.1. Ultimately, a practical example was utilized to demonstrate the utilization of the pelleted vegetable seed bonded-particle model and the DEM-CFD coupling approach in analyzing the accuracy of the seeding process in the air-suction seed-metering device. This example will serve as a valuable reference point for future field studies. Full article

Nowadays, rapid development has been achieved with respect to the electric wheel loader (EWL). The operational efficiency of EWLs is affected by many factors; especially, shovel force is a very important factor. For large-tonnage EWLs, when employing empirical, formula-based methods to predict shovel force, the generated errors are significant, with errors frequently reaching levels of up to 30%. To solve this problem, a method, based on the discrete element method (DEM), to predict shovel force is put forward in this paper. The material parameters are calibrated by a backpropagation (BP) neural network learning algorithm (NNLA). The material model is inputted into multi-body-dynamics software. A simulation model to accurately predict the shovel force is created. The error between the test results and the simulation results is 7.8%, demonstrating a high level of consistency. To validate the reliability of this method, the 35-ton EWL is taken as an example for research, and the straight-line driving test and the power-matching test are conducted. While ensuring the operational efficiency of the EWLs, the power loss is also a crucial consideration. The drastic changes in shovel force often result in front-tire slippage of the EWLs. To minimize wheel slippage during the shoveling section, the matching of the electric motor was optimized. In summary, material parameters were calibrated using a combined method of BP NNLA to predicate shovel force of a large-tonnage EWL. Additionally, the power matching of the EWL has been optimized to accord with the shoveling section of the device. Full article

This paper presents a design methodology for a low-power, low-chip-area, and high-resolution successive approximations register (SAR) analog-to-digital converter (ADC). The proposed method includes a segmented capacitive DAC (C-DAC) to reduce the power consumption and the total area. An embedded self-calibration algorithm based on a set of trimming capacitors was applied alongside a dynamic element matching (DEM) procedure to control the inherent linearity issues caused by the process mismatch. The SAR ADC and each additional algorithm were modeled in MATLAB to show their efficiency. Finally, a simple methodology was developed to allow for the fast estimation of signal-to-noise ratios (SNRs) without any FFT calculation. Full article

This paper presents a discrete-time zoom analog-to-digital converter (ADC) for low-bandwidth high-precision applications. It uses a coarse-conversion 5-bit asynchronous self-timed SAR ADC combined with a fine-conversion second-order delta-sigma modulator to efficiently obtain a high signal-to-noise distortion ratio (SNDR). An integrator circuit using a high-gain dynamic amplifier is proposed to achieve higher SNDR. The dynamic amplifier uses a switched tail current source to operate periodically, simplifying the common-mode feedback circuit, reducing unnecessary static current, and improving the PVT robustness. Dynamic error correction techniques, such as redundancy, chopping, and dynamic element matching (DEM) are used to achieve low offset and high linearity. And a 2-bit asynchronous SAR quantizer with an embedded feed-forward adder is used in the second-order delta-sigma modulator to reduce the quantization noise caused by redundancy, and further achieve higher energy efficiency. Simulation results show that the ADC achieves a peak SNDR of 121.1 dB in a 390 Hz bandwidth at a 200 kHz sampling clock while consuming only 170 $\mathsf{\mu }$W from a 2.5 V supply and the core area is 0.55 mm${}^2$. This results in a Schreier figure of merit (FoM) of 184.7 dB. Full article

This article presents an energy-efficient BJT-based temperature sensor. The output of sensing front-ends is modulated by employing an incremental $\Delta$-$\mathsf{\Sigma }$ ADC as a readout interface. The cascoded floating-inverter-based dynamic amplifier (FIA) is used as the integrator instead of the conventional operational transconductance amplifier (OTA) to achieve a low power consumption. To enhance the accuracy, chopping and dynamic element matching (DEM) are applied to eliminate the component mismatch error while $\beta$-compensation resistor and optimized bias current are used to minimize the effect of $\beta$ variation. Fabricated in a standard 180-nm CMOS process, this sensor has an active area of 0.13 mm${}^2$. While dissipating only 45.7 $\mathsf{\mu }$W in total, the sensor achieves an inaccuracy of ±0.8 °C (3$\sigma$) from −50 °C to 150 °C after one-point calibration. Full article

Herein, we present a noise shaping successive-approximation-register (SAR) analog-to-digital converter (ADC) with an embedded passive gain multiplication technique. The noise shaping moves the in-band quantization noise from the signal band to out-of-band for improved signal-to-noise ratio (SNR). The proposed approach tackles the drawback of the previous active noise shaping (increased power and extra noise) and passive noise shaping (limited noise suppression and signal loss). Both noise shaping and gain multiplication are realized on-chip in an energy-efficient manner without an opamp. This approach uses only capacitors and switches in the finite impulse response (FIR) and infinite impulse response (IIR) filters. A comparator suppressing kickback noise is presented to handle the tradeoff between noise suppression and the filter capacitor size. The energy-efficient merged-capacitor switching (MCS) technique is effectively combined with rail-to-rail swing comparator and thermometer-coded capacitor array, which reduces the settling error in the digital to analog converter (DAC). The process-induced mismatch effect in the capacitive DAC is investigated using a behavioral model of the ADC. Additionally, we propose dynamic element matching (DEM) for the thermometer-coded capacitor array. The ADC is fabricated using a 0.18 μm CMOS process in an area of 0.26 mm². Consuming 4.1 μW, the ADC achieves a signal-to-noise and distortion ratio (SNDR) of 66.5 dB and a spurious-free dynamic range (SFDR) of 79.1 dB. The figure-of-merit (FoM) of the ADC is 11.8 fJ/conversion-step. Full article

Hydraulic fracturing is a well-known production intensification technique in the petroleum industry that aims to enhance the productivity of a well drilled mostly in less permeable reservoirs. The process’s effectiveness depends on the achieved fracture conductivity, the product of fracture width, and the permeability of the proppant pack placed within the fracture. This article presents an innovative method developed by our research activity that incorporates the benefit of the Discrete—and Finite Element Method to describe the in situ behavior of hydraulic fractures with a particular emphasis on fracture conductivity. DEM (Discrete Element Method) provided the application of random particle generation and non-uniform proppant placement. We also used FEM (Finite Element Method) Static Structural module to simulate the elastic behavior of solid materials: proppant and formation, while CFD (Computational Fluid Dynamics) module was applied to represent fluid dynamics within the propped fracture. The results of our numerical model were compared to data of API RP-19D and API RP-61 laboratory measurements and findings gained by publishers dealing with propped fracture conductivity. The match of the outcomes verified the method and encouraged us to describe proppant deformation and embedment and their effect as precisely as possible. Based on the results, we performed sensitivity analysis which pointed out the impact of several factors affecting proppant embedment, deformation, and fracture conductivity and let one be aware of a reasonable interpretation of propped hydraulic fracture operation. However, DEM–CFD coupled models were introduced regarding fracturing before, to the best of our knowledge, the developed workflow of coupling DEM–FEM–CFD for modeling proppant-supported fracture behavior has not been applied yet, thus arising new perspectives for explorers and engineers. Full article

This paper presents a potentiostat readout circuit with low-noise and mismatch-tolerant current mirror using chopper stabilization and dynamic element matching (DEM) for electrochemical sensors. Current-mode electrochemical sensors are widely used to detect the blood glucose and viruses in the diagnosis of various diseases such as diabetes, hyperlipidemia, and the H5N1 avian influenza virus (AIV). Low-noise and mismatch-tolerant characteristics are essential for sensing applications that require high reliability and high sensitivity. To achieve these characteristics, a proposed potentiostat readout circuit is implemented using the chopper stabilization scheme and the DEM technique. The proposed potentiostat readout circuit consists of a chopper-stabilized programmable gain transimpedance amplifier (TIA), gain-boosted cascode current mirror, and a control amplifier (CA). The chopper scheme, which is implemented in the TIA and CA, can reduce low frequency noise components, such as 1/f noise, and can obtain low-noise levels. The mismatch offsets of the cascode current mirror can be reduced by the DEM operation. The proposed current-mirror-based potentiostat readout circuit is designed using a standard 0.18 μm CMOS process and can measure the sensor current from 350 nA to 2.8 μA. The input-referred noise integrated from 0.1 Hz to 1 kHz is 21.7 pA_RMS, and the power consumption was 287.9 μW with a 1.8 V power supply. Full article

Deep horizontal high stress and high permeability geological factors appear when coal mines are converted to deep horizontal mining. When the roadway is damaged by the mining face, and the supporting components are mismatched, the deep roadways necessitate extensive repair work, which has a negative impact on the coal mining economy and sustainability. This paper carried out a series of field tests on the roadways deformation, crack distribution, and loose rock zone of the deep roadways. Furthermore, a numerical calculation model was established using the discrete element method (DEM) and calibrated with laboratory tests and RQD methods. Both the stress and crack distribution in the surrounding rock of the deep roadway were simulated. The field test and the corrected numerical model showed consistency. A FISH function was used to document the propagation of shear and tensile cracks around the roadway in three periods, and a damage parameter was adopted to evaluate the failure mechanism of the deep roadways under the dynamic stress disturbance. The matching of specifications of anchor cables, rock bolts, and anchoring agent is the primary point in the control of deep roadways, and revealing the stress evolution, crack propagation, and damage distribution caused by mining effects is another key point in deep roadway controlling. The field test and DEM in this paper provide a reference for the design of surrounding rock control of deep roadways and the sustainable development of coal mines. Full article

The electrification of loader designs can utilise several power motor types. Hence, this study investigates the operational performance of pure electric-powered loaders matched with three types of motors. Firstly, for the ZL08 loader, it is proposed that a pure electric-powered loader structure adopts two motors to drive the walking and hydraulic systems separately. Secondly, the dynamic parameters of the two motors were matched, and then, a joint vehicle dynamics model of the control system, the Multi-Body Dynamics (MBD) module and the material Discrete Element Method (DEM) module, was established. Finally, the performance of the walking system with three motors was tested by inserting three materials and using accelerating and climbing methods. The operating performance of the hydraulic system was tested by shovelling and unloading three materials. Results show that when inserting difficult materials, the loader’s walking system with switched reluctance motors is 9.74–21.2% deeper than that with the other two motors and 11.7–56.2% faster at the same depth. The hydraulic system consumes 3–15.7% less energy when matched with a permanent magnet synchronous motor than the other two motors. Pure electric loaders have the best operating performance when the walking system is matched with a switched reluctance motor, and the hydraulic system is matched with a permanent magnet synchronous motor. Full article

CFD-DEM (computational fluid dynamic-discrete element method) is a promising approach for simulating fluid–solid flows in fluidized beds. This approach generally under-predicts the granular temperature due to the use of drag models for the average drag force. This work develops a simple model to improve the granular temperature through increasing the drag force fluctuations on the particles. The increased drag force fluctuations are designed to match those obtained from PR-DNSs (particle-resolved direct numerical simulations). The impacts of the present model on the granular temperatures are demonstrated by posteriori tests. The posteriori tests of tri-periodic gas–solid flows show that simulations with the present model can obtain transient as well as steady-state granular temperature correctly. Moreover, the posteriori tests of fluidized beds indicated that the present model could significantly improve the granular temperature for the homogenous or slightly inhomogeneous systems, while it showed negligible improvement on the granular temperature for the significantly inhomogeneous systems. Full article

This article presents in-pixel (of a CMOS image sensor (CIS)) temperature sensors with improved accuracy in the spatial and the temporal domain. The goal of the temperature sensors is to be used to compensate for dark (current) fixed pattern noise (FPN) during the exposure of the CIS. The temperature sensors are based on substrate parasitic bipolar junction transistor (BJT) and on the nMOS source follower of the pixel. The accuracy of these temperature sensors has been improved in the analog domain by using dynamic element matching (DEM), a temperature independent bias current based on a bandgap reference (BGR) with a temperature independent resistor, correlated double sampling (CDS), and a full BGR bias of the gain amplifier. The accuracy of the bipolar based temperature sensor has been improved to a level of ±0.25 °C, a 3σ variation of ±0.7 °C in the spatial domain, and a 3σ variation of ±1 °C in the temporal domain. In the case of the nMOS based temperature sensor, an accuracy of ±0.45 °C, 3σ variation of ±0.95 °C in the spatial domain, and ±1.4 °C in the temporal domain have been acquired. The temperature range is between −40 °C and 100 °C. Full article

Sorted stone circles are natural surface patterns formed in periglacial environments. Their relation to permafrost conditions make them very helpful for better understanding the past climates where they were formed and have evolved and also for monitoring current underlying processes in case circles are active. These metric scale patterns that occur in clusters of tens to thousands of circular elements, can be more comprehensively characterized if automated methods are used. This paper addresses their identification and delineation through the development and testing of a set of automated approaches, namely, template matching, sliding band filter, and dynamic programming. All of these methods take advantage of the 3D shape of the structures conveyed by digital elevation models (DEM), built from ultra-high resolution imagery captured by unmanned aerial vehicles (UAV) surveys developed in Barton Peninsula, King George Island, Antarctica (62°S). The best detection results achieve scores above 85%, while the delineations are performed with errors as low as 7%. Full article