Wide Operating Range Research Articles

Kilowatt high power ytterbium-doped fiber laser operation in a record wide temperature range from -50 ℃ to 50 ℃

Kilowatt high power ytterbium-doped fiber laser operation in a record wide temperature range from -50 ℃ to 50 ℃

Model-Based Assessment of Energy Efficiency in Industrial Pump Systems: A Case Study Approach

Outdated, oversized variable speed pump drives (VSDPs) in industry lead to sub-optimal energy efficiency and considerable energy losses. This paper proposes methods to develop 2D efficiency maps for motors, converters, and pumps using polynomial surface fitting, which enables efficiency evaluation in a wide operating range. The method was applied to an oversized VSDP in an industrial chilled water supply system, comparing the original system with five alternative VSDP combinations with high-efficiency motors and pumps. The five VSDP variants demonstrated average energy savings of around 30%, with the synchronous reluctance motor (SRM) configurations outperforming the induction motor (IM) configurations by up to 7 percentage points, particularly at low loads. The high-efficiency SRM-based 252-IE5 variant delivered the best overall energy performance, highlighting the benefits of optimised system sizing and motor selection for energy savings. The proposed method can be used in both industrial and residential applications and offers great advantages in process systems that require variable flow and pressure of water or other fluids during operation, such as HVAC, water supply and wastewater treatment, district heating, etc. The development of a VSDP drive with efficient energy optimisation is an interdisciplinary problem of mechanical and electrical engineering, and without the interaction of engineers from both fields the result will not be optimal. We try to present our method so that it can be a reliable tool for mechanical, electrical, and other engineers or researchers to assist them in finding possible energy savings, performing energy audits, and selecting the most suitable components when modernising existing or developing new systems.

Anion‐Anchored Polymer‐in‐Salt Solid Electrolyte for High‐Performance Zinc Batteries

AbstractSolid polymer electrolytes hold promise for addressing key challenges in rechargeable zinc batteries (ZBs) utilizing aqueous electrolytes. However, achieving simultaneous high ionic conductivity, excellent mechanical strength, and a high cation transference number while effectively suppressing Zn dendrites remains challenging. Herein, we design a novel polymer‐in‐salt solid electrolyte (PISSE) composed of polyacrylonitrile (PAN), zinc chloride (ZnCl2), and niobium pentoxide with oxygen vacancies (Nb2O5‐x) with high ionic conductivity. PAN polymer matrix provides the electrolyte good mechanical properties and solubility of Zn salt. The high concentration of ZnCl2 effectively decouples the Zn2+ from polymer chain segments and provides more ionic conduction amorphous region. Moreover, incorporating Nb2O5‐x filler accelerates Zn2+ desolvation by anchoring (ZnxCly)2x–y clusters and enhances the system's mechanical properties, achieving a superior Zn2+ transference number (~0.93) and interfacial stability. Consequently, the optimized PISSE demonstrates exceptional stability during prolonged cycling periods, wide temperature range operation (−40 °C to 60 °C), remarkable flexibility, and compatibility with diverse electrode materials. This study provides valuable insights into the design of solid‐state electrolytes based on ZBs and elucidates their multifunctional prospects.

Dynamic modeling of post-combustion carbon capture process based on multi-gate mixture-of-experts incorporating dual-stage attention-based encoder-decoder network

Solvent-based post-combustion carbon capture (PCC) technology is a promising, near-term solution for decarbonizing power generation and industrial facilities. Model-based process simulation is crucial for the optimal design and operation of the PCC process. Recently, data-driven models have gained attention due to their adaptability, efficient computation and high accuracy. However, the nonlinearity, strong couplings and multi-time scale features of the PCC process pose significant challenges for model identification. To this end, this paper proposes a multi-gate mixture-of-experts incorporating dual-stage attention-based encoder-decoder (MMoE-DAED) network for dynamic modeling of the PCC process under wide operating conditions. An encoder-decoder composed of long short-term memory (LSTM) network is employed to extract features from the time-dependent input data and learn the complex dynamic interactions caused by the inertial and delay properties of the process. Dual-stage attention mechanism is incorporated into the encoder and decoder respectively to select the most relevant input features and their correlations within the time series data. To enhance multi-output prediction accuracy, multi-gate mixture-of-experts (MMoE) framework that considers correlations of multitask learning is implemented. Simulation results using operating data from a PCC experimental setup indicate that the proposed modeling approach accurately predicts the steady-state values and dynamic trends of the CO2 capture rate and stripper bottom temperature over a wide operating range. The RMSE, MAPE and R2 indices for the CO2 capture rate are 2.1592, 0.0295, 0.9641, respectively, and for the stripper bottom temperature are 0.1491, 0.0003, 0.9833, respectively. Validations on a PCC simulator further verify the accuracy and efficiency of the MMoE-DAED model, which enables an 80.87% reduction in computation time compared to the simulator. This paper points to a new direction for the data-driven dynamic modeling of complex energy conversion processes.

Self-priming dumbbell probe-mediated cascade isothermal amplification for sensitive and label-free MICRORNA detection using fluorescence light-up silver nanocluster

Given the critical significance of microRNAs (miRNAs) in cancer diagnosis and classification (e.g., glioma), there is a need for the advancement of sensitive, specific, quantitative, and cost-effective approach for assessing miRNA expression levels. We present an effective amplification technology for ultrasensitive miRNA analysis by combining a self-priming dumbbell probe-mediated cascade isothermal amplification strategy with fluorescence-enhanced silver nanoclusters (DNA-AgNCs). The approach depends on the disassociation of the stem portion of the dumbbell probe through the binding of target miRNA, followed by self-priming mediated target recycling, DNA polymerase/endonuclease facilitated chain extension, and catalytic hairpin assembly (CHA) to provide an amplified signal. The CHA procedure generates an LP-AgNCs/LP-G duplex, wherein the fluorescence signals of DNA-AgNCs can be significantly amplified when in close proximity to guanine-rich (G-rich) DNA sequences. The proposed label-free assay, characterized by high sensitivity, a wide dynamic range (spanning 6 orders of magnitude), excellent specificity (capable of detecting single-base differences), and simple operation, has been successfully utilized for the detection of miRNA in real samples. This demonstrates its potential as a compelling alternative for miRNA analysis in gene expression profiling and molecular diagnostics, especially for early glioma cancer detection.

Wide-Range Operation of Microwave Photonic Sensor Using Recurrent Neural Network

Wide-Range Operation of Microwave Photonic Sensor Using Recurrent Neural Network

Continuous Graded Catalyst Layers for PEM Fuel Cells with Improved Humidity Range Tolerance

Abstract Grading electrodes is a promising approach to reduce ohmic and mass transport-related voltage losses in proton exchange membrane fuel cells. In graded electrodes, the ionomer and/or catalyst are spatially non-uniformly distributed to optimize performance over a wide operating range. In this study, through-plane ionomer gradients were fabricated with a simple wet-layer deposition technique that can readily be adapted in a roll-to-roll process. The presence of ionomer gradients was verified using scanning transmission electron microscopy and the profiles were found to be continuous despite using only two coating steps. Single cell tests revealed that the gradients outperform conventional electrodes and maintain the optimal performance for different relative humidities. These improvements were traced back to enhanced mass transport and protonic conduction properties identified by detailed electrochemical analysis. This manufacturing approach for electrodes offers an accessible toolbox to produce versatile and specialized multi-layered catalyst layers for different applications.

Promotion of Single-Electron Transfer by Low-Coordinated Co Single Atoms to Facilitate Advanced Oxidation Processes in Wastewater Treatment.

Heterogeneous catalysts are fascinating for advanced oxidation processes (AOPs) in wastewater treatment to reduce cost, metal contamination, and pH operation limitations. However, they usually encounter low catalytic efficiency because of the difficult single-electron-transfer (SET) pathway during AOPs. Herein, an efficient heterogeneous catalyst for AOPs is realized through the rational regulation of N coordination around Co single-atom (SA) centers in favor of SET. As guided by calculations, low N coordination enables a high density of electronic states at the Fermi energy level of SA Co to facilitate SET activation of peroxomonosulfate (PMS). A special oxide-compounding method is further applied to decrease the N coordination of SA Co on the carbon carriers from common Co1-N3/4 to the desired Co1-N2. Co1-N2 shows a delightful activity for AOP degradation of various organic pollutants with kinetic rate and turnover frequency values up to 0.862 min-1 and 389 h-1, respectively, greatly outperforming those of Co1-N3/4. It is also superior in a wide pH operation range and has strong resistance to environmental disturbances. Detailed mechanistic investigations confirm the generation of singlet oxygen (1O2) instead of common radical O species from the SET between PMS and Co1-N2, corroborating the calculated results and accounting for the enhanced AOP activity.

Development of a potentiometric sensor for mercury (II) ion using cerium (IV) tinmolybdophosphate

ObjectivesThe primary objective of this report is to develop a heperopolyacid salt, Cerium (IV) tinmolybdophosphate (CeSnMoP), with distinctive attributes that significantly enhance its ion exchange capacity. Through deliberate adjustments in temperature, pH, and volume ratios, we have carefully prepared a range of CeSnMoP samples. One sample exhibiting an ion exchange capacity (IEC) of 5.06 ± 0.2 meq gm-1 has been identified for further extensive analysis. The second objective was to develop the potentiometric sensor by using the synthesised sample therefore it was transformed into an electrode incorporating PVC as binder material and validated as a potentiometric sensor for Mercury ions which can work as variable media.Data descriptionInstrumental analyses, such as XRD, IR, TGA, SEM and EDS, were used to elucidate the compound’s structural aspects. Distribution coefficient (Kd) studies highlighted the compound's pronounced selectivity towards Hg2+ ions. This catalyst was further utilized as an electro-active substance for detecting Hg2+ ions in an external solution. Epoxy resin played the role of a binder in the electrode formulations. The electrode, comprising a membrane with 50% exchanger material, demonstrated superior performance. This selected membrane exhibited a wide operational concentration range of 1 × 10–6 M – 1 × 10–1 M of Hg2+ ions for quantitative analysis of unknown samples of mercury ions. The lower detection limit for the calibration curve was recorded up to 2 × 10–8 M from 1 to 10–1 M. The electrode effectively sensed this metal ion within the pH range of 3.74–7.51 and exhibited a lifespan exceeding 8 months.

A hydrogel sensor based on conic baston structure

AbstractResistive flexible pressure sensors are extensively employed in wearable devices owing to their wide operational range and straightforward construction. This study presents a conic bastion‐structured sensor microunit to improve the sensor sensitivity. The base hydrogel is synthesized using acrylamide (AM), with Mg2+ and Na+ acting as conductive ions. The sensor is fabricated using digital light processing (DLP) 3D printing technology and is subjected to experimental evaluation. The findings indicate that the hydrogel sensor with a 50 wt% AM composition demonstrates enhanced mechanical strength and conductive properties, achieving a peak sensitivity of 0.534 kPa−1 within a pressure range of 0–0.8 kPa. Furthermore, the sensor exhibits favorable response characteristics (30 ms) and recovery characteristics (40 ms), along with stability. The proposed sensor is suitable for wearable devices and live joint angle detection. Additionally, the “handwriting fingerprint” pattern recognition and document verification proposed in this article make it applicable in scenarios, such as banking, notarization, and other handwriting and seal verification contexts.

Influence of the Depth of Shallow Workings on the Probability of Sinkhole Formation and Determination of the Contribution of Mines to the Resulting Risk

AbstractThis paper presents a broad spectrum of factors that have an impact on the environment once underground mines have been closed, with particular emphasis on hard coal mines. Based on the review of scientific literature and own experience, several types of environmental impacts of closed mines were specified. In the author’s opinion, sinkholes pose the most serious hazard to post-mining areas. A high degree of urbanisation of the Upper Silesian Coal Basin and a wide range of mining operations conducted in the past necessitate the post-mining areas development for construction purposes. However, investing in these areas cannot carry risks and pose a threat to public safety. Therefore, a simplified method of determining the probability of sinkhole formation depending on the depth of a shallow void (excavation) in the rock mass was proposed. An algorithm has also been proposed for determining the contribution of individual mining companies to causing sinkhole hazard, which is of great importance in legal proceedings.

Bubble generation in a 3-D flow-focusing microchannel: From squeezing to jetting

Fine bubbles have been applied in many fields; however, the controllable preparation of monodispersed fine bubbles remains a challenge. In this study, a three-dimensional (3-D) flow-focusing microfluidic device was designed. Compared with bubble formation in one-dimensional (1-D) and two-dimensional (2-D) flow-focusing, the 3-D flow-focusing microchannel owns the features of making bubbles with much smaller sizes and wider operation range. Four different gas–liquid flow regimes (squeezing, squeezing-dripping transition, dripping, and jetting) and three different gas–liquid dispersion states (mono-dispersion, bi-dispersion, and poly-dispersion) were observed in the 3-D flow-focusing microchannels. Importantly, the bi-dispersion in the squeezing-dripping transition regime experimentally verified that the squeezing and viscous shearing mechanisms separately control bubble formation in the transition region based on the time sequence. The intrinsic reason for poly-dispersion in the squeezing-dripping transition and jetting regimes was revealed. Finally, a mathematical model is proposed to predict the bubble size in the flow-focusing microchannels.

NAS-BNN: Neural Architecture Search for Binary Neural Networks

Binary Neural Networks (BNNs) have gained extensive attention for their superior inferencing efficiency and compression ratio compared to traditional full-precision networks. However, due to the unique characteristics of BNNs, designing a powerful binary architecture is challenging and often requires significant manpower. A promising solution is to utilize Neural Architecture Search (NAS) to assist in designing BNNs, but current NAS methods for BNNs are relatively straightforward and leave a performance gap between the searched models and manually designed ones. To address this gap, we propose a novel neural architecture search scheme for binary neural networks, named NAS-BNN. We first carefully design a search space based on the unique characteristics of BNNs. Then, we present three training strategies, which significantly enhance the training of supernet and boost the performance of all subnets. Our discovered binary model family outperforms previous BNNs for a wide range of operations (OPs) from 20M to 200M. For instance, we achieve 68.20% top-1 accuracy on ImageNet with only 57M OPs. In addition, we validate the transferability of these searched BNNs on the object detection task, and our binary detectors with the searched BNNs achieve a novel state-of-the-art result, e.g., 31.6% mAP with 370M OPs, on MS COCO dataset. The source code and models will be released at https://github.com/VDIGPKU/NAS-BNN.

Anion-Anchored Polymer-in-Salt Solid Electrolyte for High-Performance Zinc Batteries.

Solid polymer electrolytes hold promise for addressing key challenges in rechargeable zinc batteries (ZBs) utilizing aqueous electrolytes. However, achieving simultaneous high ionic conductivity, excellent mechanical strength, and a high cation transference number while effectively suppressing Zn dendrites remains challenging. Herein, we design a novel polymer-in-salt solid electrolyte (PISSE) composed of polyacrylonitrile (PAN), zinc chloride (ZnCl2), and niobium pentoxide with oxygen vacancies (Nb2O5-x) with high ionic conductivity. PAN polymer matrix provides the electrolyte good mechanical properties and solubility of Zn salt. The high concentration of ZnCl2 effectively decouples the Zn2+ from polymer chain segments and provides more ionic conduction amorphous region. Moreover, incorporating Nb2O5-x filler accelerates Zn2+ desolvation by anchoring (ZnxCly)2x-y clusters and enhances the system's mechanical properties, achieving a superior Zn2+ transference number (~0.93) and interfacial stability. Consequently, the optimized PISSE demonstrates exceptional stability during prolonged cycling periods, wide temperature range operation (-40 ℃ to 60 ℃), remarkable flexibility, and compatibility with diverse electrode materials. This study provides valuable insights into the design of solid-state electrolytes based on ZBs and elucidates their multifunctional prospects.

Low-order-model-based design of additive-manufactured heat exchanger

Abstract This paper discusses a comprehensive approach to the design of an additive-manufactured heat exchanger for a high-temperature application. This manufacturing route is attractive because of the flexibility afforded in design, but there is a requirement for calibration of internal friction factors and heat transfer coefficients because of uncertainty regarding the characteristics of the manufactured internal surfaces. The design was informed by physics-based low-order models (total pressure loss model; conjugate heat transfer model) calibrated against experimental data. To extract heat transfer coefficients we use transient experiments performed over timescales for which the surfaces can be regarded as semi-infinite. The calibrated models are used to predict accurate performance characteristics for the heat exchanger. Experimental results for a prototype design were found to be in excellent agreement with the model over a wide operational range, validating both the design methodology and the utility of the particular design for the given application. Our process, though not unique, has wide applicability, has been conducted with considerable care, and will be of interest to those engaged in low-order-model-based heat exchanger design.

A flexible resistive strain gauge with reduced temperature effect via thermal expansion anisotropic composite substrate

Strain gauge plays vital roles in various fields as structural health monitoring, aerospace engineering, and civil infrastructure. However, traditional flexible strain gauge inevitably brings the pseudo-signal caused by the substrate temperature effect and determines its accuracy. Here, we present an anisotropic composite substrate designed to modify the thermal expansion performance via Micro-electro-mechanical System (MEMS) technology, which facilitates the development of strain gauges that are minimally affected by substrate temperature-induced effect. Compared to the isotropic flexible substrate, the simulated expansion displacement in the thermal insensitive direction is reduced by 53.6% via introducing an anisotropic thermal expansion structure. The developed strain gauge exhibits significantly reduced sensitivity to temperature-induced effect, with a temperature coefficient of resistance decreasing from 87.3% to 10%, along with a notable 47.1% improvement in TCR stability. In addition, the strain gauge displays a sensitivity of 1.99 and boasts a wide strain operational range of 0–6000 µε, while maintaining excellent linearity. Furthermore, stress response conducted on a model of an aircraft wing illustrates the rapid monitoring of the strain gauge, which can detect strain as low as 100 µε. This study strongly highlights the potential applicability of the developed strain gauge in the aircraft, ships, and bridges for monitoring stress.

Half-Wave Phase Shift Modulation for Hybrid Modular Multilevel Converter with Wide-Range Operation

Hybrid modular multilevel converters (MMCs), which combine submodule chain links and device series switches, offer advantages such as lower costs and smaller volumes compared with MMCs. However, the hybrid MMCs only operate at a fixed modulation ratio, potentially compromising system adjustment ability. This paper presents a half-wave phase shift modulation (HPSM) strategy aimed at extending the operation range of a hybrid MMC. First, the commutation angle is introduced as a control variable to change the fixed voltage modulation ratio. The energy balance of the converter is completed by adjusting the commutation angle. Then, the operation performance for the half-wave alternating multilevel converter (HAMC) with the proposed HPSM strategy is analyzed. Finally, the full-scale simulations are carried out to verify the theoretical analysis and the feasibility of the proposed control strategy. Compared to the third-order harmonic current injection (THCI) strategy, HPSM reduces operating losses by 50% and demonstrates superior control performance.

Three-Phase Electrolytic-Capacitor-Less LCC-S WPT System With Wide Operation Range

Three-Phase Electrolytic-Capacitor-Less LCC-S WPT System With Wide Operation Range

Numerical assessment of transient flow and energy dissipation in a Pelton turbine during startup

The Pelton turbine, known for its high application water head, wide efficient operating range, and rapid start-stop capability, is ideal for addressing intermittent and stochastic load issues. This study numerically analyzes the transient two-phase flow and energy dissipation during the startup of a Pelton turbine. Dynamic mesh technology controlled nozzle opening changes, and momentum balance equations managed runner rotation. Findings showed that the runner speed initially increased rapidly and then more slowly, and flow rate matched the nozzle opening variations. Runner torque first rose linearly, then decreased, with the fastest decline during nozzle closing. Hydraulic efficiency peaked early in nozzle reduction but then dropped sharply. Strong vortices formed due to upstream inflow and downstream backflow impact in the distributor pipe. The jet needle and guide vane improved flow in the converging section of nozzle, but flow began to diffuse with increased stroke. Initially, the jet spread fully on the bucket surface, but later only affected the bucket tips. Pressure fluctuations in the water supply mechanism were primarily due to jet needle motion, with higher amplitude during movement and lower when stationary. These fluctuations propagated upstream, weakening over distance. Reynolds stress work and turbulent kinetic energy generation, respectively, dominated energy transmission and energy dissipation, with their maximum contribution exceeding 96% and 70%. High-energy clusters corresponded to jet impact positions, highlighting jet-bucket interference as crucial for energy transport. This study established a performance evaluation method for Pelton turbine startups, supporting further investigation into characteristic parameters, flow evolution, and energy dissipation patterns.

New disturbance observer-based speed estimator for induction motor

<p>This paper discusses a novel disturbance observer designed as an estimator to determine the rotor speed of an induction motor. This observer is a solution to obtain a simple structure with a small number of compact observer gains. Furthermore, the adaptation law is no longer required to estimate induction motor speed values. This is a machine model-based computation method that uses a stationary reference frame. The nonlinearity problem is solved using an additional state vector in the observer model, which is known as an extended state observer. This approach easily and systematically determines the observer gain by applying the linear quadratic regulator (LQR) method, thereby avoiding time-consuming trial errors. The proposed observer, which was presented in both continuous and discrete forms, was tested using a sensorless V/f- controlled induction motor. The simulation results show that the proposed observer can accurately estimate all states, namely, the rotor flux and stator current; therefore, the proposed estimator provides the speed and electromagnetic torque for a wide operational range of speeds and load torques. It was also shown that the proposed observer was robust to noise and uncertainty in induction motor parameters.</p>