Search Results (1,639)

This paper presents a passive wireless temperature sensor based on an SS-compensated LC-thermistor topology. The system consists of two magnetically coupled LC tanks—each composed of a coil and a series capacitor—forming a series–series (SS) compensation network. The secondary side includes a negative temperature coefficient (NTC) thermistor connected in series with its coil and capacitor, acting as a temperature-dependent load. Magnetically coupled resonant systems exhibit different coupling regimes: weak, critical, and strong. When operating in the strongly coupled regime, the original resonance splits into two distinct frequencies—a phenomenon known as bifurcation. At these split resonance frequencies, the load impedance on the secondary side is reflected as pure resistance at the primary side. In the SS topology, this reflected resistance is equal to the thermistor resistance, enabling precise wireless sensing. The advantage of the SS-compensated configuration lies in its ability to map changes in the thermistor’s resistance directly to the input impedance seen by the reader circuit. As a result, the sensor can wirelessly monitor temperature variations by simply tracking the input impedance at split resonance points. We experimentally validate this property on a benchtop prototype using a one-port VNA measurement, demonstrating that the input resistance at both split frequencies closely matches the expected thermistor resistance, with the observed agreement influenced by the parasitic effects of RF components within the tested temperature range. We also demonstrate that using the average readout provides first-order immunity to small capacitor drift, yielding stable readings. Full article

During the operation of steel cable-driven radiation-resistant robots in nuclear industrial environments, the tensile force of a steel cable is influenced by temperature variations, which can cause significant detection errors. To address this problem, this study proposes a temperature-compensated axial force characterization method for steel cables based on the magnetoelastic effect, aiming to ensure the measurement accuracy of magnetoelastic sensors. The principle of the magnetoelastic measurement method involves magnetizing the steel cable. When subjected to tensile forces, the magnetization characteristics of the steel cable change, thereby altering the detection signal of the magnetoelastic sensor. By analyzing the relationship between steel cable tension and variations in the detection signal, effective force measurement can be achieved. First, experiments are conducted to investigate the influence of temperature on the detection signals of a magnetoelastic sensor under zero-load conditions. Then, additional tests are performed to examine the combined effects of a tensile force and temperature on the sensor’s signals. Finally, based on the experimental data, axial force prediction models are constructed using both surface fitting and a backpropagation neural network (BPNN). The results demonstrate that, compared to the resistance values, inductance exhibits superior stability under temperature variations. In the temperature range of 20–50 °C, the inductance variation is approximately 0.15 μH, which indicates improved suitability for characterizing the axial force of steel cables. It is also shown that under isothermal conditions, the inductance increases linearly with the applied tensile force, exhibiting a slope of approximately 0.025 μH/kN. Both the surface fitting-based and BPNN-based axial force prediction models demonstrate high accuracy, with absolute prediction errors consistently below 5% compared to actual data. Full article

The significant negative thermal expansion (NTE) that occurs in La(Fe,Si)₁₃-based alloys during magnetic transition make them promising to combine with positive thermal expansion (PTE) materials to obtain near-zero thermal expansion (NZTE) materials. However, La(Fe,Si)₁₃-based alloys with NTE generally show intrinsic poor mechanical properties. Here, thermal expansion properties are optimized by adding Ag in La_0.6Ce_0.4(Fe_0.91Co_0.09)_11.9Si_1.1 to form a multi-phase structure exhibiting enhanced compressive strength. Through spark plasma sintering (SPS) and annealing, the samples consisted of α-Fe(Co,Si), NaZn₁₃-type, and LaAg₂ phases. When the annealing temperature reaches 1323 K, LaAg₂ disappears and is replaced by La₂O₃. The LaAg₂ phase and α-Fe(Co,Si) phase contribute as PTE materials to compensate for the NTE of the NaZn₁₃-type phase. Near-zero thermal expansion was achieved in the temperature range of 240–294 K, with a coefficient of thermal expansion (CTE) of 3.5 ppm/K at a 9.581 at.% Ag content. Benefiting from the uniform phase distribution and coordinated deformation, the samples obtained high mechanical strengths, with fracture stresses of 1481.1 MPa for the 15 wt.% Ag sample. This work provides a promising route for high-strength and near-zero thermal expansion Ag/La(Fe,Si)₁₃ composites. Full article

In oil well environments, pressure sensors are often challenged by electromagnetic interference, temperature drift, and corrosive fluids, which reduce their stability and service life. To improve long-term reliability under these conditions, we developed a fiber optic Fabry–Perot (FP) cavity pressure sensor that employs an Inconel 718 diaphragm to provide both high mechanical strength and corrosion resistance. An integrated fiber Bragg grating (FBG) was included to monitor temperature simultaneously, allowing temperature–pressure cross-sensitivity to be decoupled. The sensor was fabricated and tested over a temperature range of 20–100 °C and a pressure range of 0–60 MPa. Experimental characterization showed that the FP cavity length shifted linearly with pressure, with a sensitivity of 377 nm/MPa, while the FBG demonstrated a temperature sensitivity of 0.012 nm/°C. After temperature compensation, the overall pressure measurement accuracy reached 0.5% of the full operating pressure range (0–60 MPa). These results confirm that the combined FP–FBG sensing approach maintained stable performance in harsh downhole conditions, making it suitable for pressure monitoring in shallow and medium-depth reservoirs. The proposed design offers a practical route to extend the operational lifetime of optical sensors in oilfield applications. Full article

This paper presents a high-sensitivity multi-point seawater temperature detection system based on the virtual Vernier effect, achieved through multiplexed Fabry–Perot (FP) cavities combined with optical frequency-modulated continuous wave (FMCW) interferometry. To address the nonlinear frequency scanning issue inherent in FMCW systems, this paper implemented a software compensation method. This approach enables accurate positioning of multiple FP sub-sensors and effective demodulation of the sensing interference spectrum (SIS) for each FP interferometer (FPI). Through digital signal processing (DSP) algorithms and spectral demodulation, each sub-FP sensor generates an artificial reference spectrum (ARS). The virtual Vernier effect is then achieved by means of a computational process that combines the SIS intensity with the corresponding ARS intensity. This eliminates the need for physical reference arrays with carefully detuned spatial frequencies, as is required in traditional Vernier effect implementations. The sensitivity amplification can be dynamically adjusted with the modulation function parameters. Experimental results demonstrate that an optical fiber link of 82.3 m was achieved with a high spatial resolution of 23.9 $\mathsf{\mu }\mathrm{m}$. Within the temperature range of ${30 }^{\circ }\mathrm{C}$ to ${70 }^{\circ }\mathrm{C}$, the temperature sensitivities of the three enhanced EIS reached −275.56 $\mathrm{pm}{/}^{\circ }\mathrm{C}$, −269.78 $\mathrm{pm}{/}^{\circ }\mathrm{C}$, and −280.67 $\mathrm{pm}{/}^{\circ }\mathrm{C}$, respectively, representing amplification factors of 3.32, 4.93, and 6.13 compared to a single SIS. The presented approach not only enables effective multiplexing and spatial localization of multiple fiber sensors but also successfully amplifies weak signal detection. This breakthrough provides crucial technical support for implementing quasi-distributed optical sensitization sensing in marine environments, opening new possibilities for high-precision oceanographic monitoring. Full article

During the transition from urban expansion to renewal, optimizing environmental comfort under resource constraints presents critical challenges. While existing research confirms that multisensory interactions critically shape environmental comfort, these insights are rarely operationalized into protocols for resource-constrained contexts. Focusing on historic urban quarters that need to balance modification and preservation, this study quantifies multisensory (acoustic, visual, thermal) interactions and integrations to establish operational resource-optimization strategies. Through laboratory reproduction of 144 field-based experimental conditions (4 sound sources × 3 sound pressure levels × 4 green view indexes × 3 air temperatures), systematic subjective evaluations of acoustic, visual, thermal, and overall comfort were obtained. Key findings demonstrate: (1) Eliminating extreme comfort evaluations (e.g., “very uncomfortable”) within any single sensory domain stabilizes cross-sensory contributions to overall comfort, ensuring predictable cross-domain compensations and safeguarding resource efficacy; (2) Accumulating modest improvements across ≥2 sensory domains reduces per-domain performance threshold for satisfactory overall comfort, enabling constraint resolution (e.g., visual modification limits in historic districts); (3) Cross-domain optimization of environmental factors (e.g., sound source and air temperature) generates mutual enhancement effects, maximizing resource economy, whereas intra-domain optimization (e.g., sound source and sound pressure level) induces competitive inefficiencies. Collectively, these principles establish operational strategies for resource-constrained environmental improvements, advancing sustainable design and governance through evidence-based multisensory approaches. Full article

This work provides a comparison of two commercial carbon fiber reinforced plastic (CFRP) materials: HexPly^® M18 1/G939 and RTM6/G939. Differences due to the additional thermoplastic in one CFRP are investigated for the two otherwise nearly identical, aromatic epoxy-based composites with respect to thermal degradation. The scenario chosen for testing is based on real incidents of repeated overheating by hot gases between roughly 200 and 320 °C, leading to moderate thermal damage. A special test setup is designed to continuously and alternately load CFRP with hot air in a rapid change. Post-mortem analysis is performed by mass loss, ultrasonic, and mechanical testing. Polymer degradation is analyzed by infrared spectroscopy. Even if the temperature-resistant thermoplastic polyetherimide (PEI) in the M18-1 matrix is enriched between the plies and a compensation of thermal strain during rapid temperature changes is expected, only a weak improvement is observed for residual strength in the presence of PEI, for continuous as well as alternating thermal loading. Thermally induced delaminations are even more pronounced in M18-1/G939. Deep insight is gained into degradation after repeated overheating of CFRP within the chosen scenario. Multivariate data analyses based on infrared spectroscopy allow for the determination of thermal history and residual strength, valuable for failure analysis. Full article

Accurate and real-time monitoring of low-frequency electromagnetic field (EMF) is essential in power and industrial environments, yet most conventional approaches still suffer from limited spatial coverage, manual operation, and insufficient digitization. To address these challenges, this paper proposes an intelligent EMF monitoring system that integrates six-axis magnetic field sensing, temperature compensation, vector synthesis, Sub-1 GHz wireless communication, and real-time data visualization. The system supports simultaneous measurement of both AC and DC magnetic fields across the 30 Hz–100 kHz range, with specific optimization for power-frequency conditions (50/60 Hz). Designed with modular integration and low power consumption, it is suitable for portable deployment in field scenarios. Comprehensive laboratory and substation tests demonstrate high accuracy, with maximum measurement errors of 1.17% under zero-field and 1.42% under applied-field conditions—well below the ±5% tolerance defined by international standards. Wireless performance tests further confirm stable long-distance communication, achieving ranges of up to 5 km without significant transmission errors, while overall system measurement error reached as low as 0.015%. These results verify the system’s robustness, fidelity, and compliance with international safety standards. Overall, the proposed platform provides a practical and scalable solution for intelligent EMF monitoring, offering strong potential for deployment in industrial environments and infrastructure-critical applications. Full article

The successful establishment of battery electric vehicles (BEVs) is strongly linked to criteria such as cost and range. In particular, the need for air conditioning strains battery capacities and limits the availability of BEVs. Thermal energy storage systems (TESs) open up alternative paths for heat and cold supply with excellent scalability and cost efficiency. Previous TES concepts have largely focused on heat during cold seasons, but storage-based air conditioning systems for all seasons are still missing. To fill this gap, a concept based on a Brayton cycle allowing heat and cold supply and, simultaneously, an output of electrical energy at times when no air conditioning is needed was investigated. Central thermal components include water-based cold storage and electrically heated, high-temperature, solid-medium storage, both with innovative TPMS structures and flexible operation managements. With transient simulation studies a system was identified with effective storage densities of up to 100 Wh/kg, reaching a constant heat and cold supply of 5 kW and 2.5 kW, respectively, over 41 min. In addition, the underlying cycle allows an electrical output of up to 1.7 kW during times of inactive air conditioning requirements. Compared to a reference system designed only for winter operation, the moderately lower storage densities are compensated by proportionately longer discharging times. By combining a compact and dynamic Brayton cycle with a TES in BEVs, a storage-based air conditioning system with high utilization potential and high operational flexibility was developed. In addition to further optimizations, the knowledge for TES solutions can also be transferred to today’s air conditioning systems, extending the solution space for storage-supported thermomanagement options in BEVs. Full article

Thrust vectoring technology significantly improves the manoeuvrability and environmental adaptability of unmanned aerial vehicles by dynamically regulating the direction and magnitude of thrust. In this paper, the principles and applications of mechanical thrust vectoring technology, fluidic thrust vectoring technology and the distributed electric propulsion system are systematically reviewed. It is shown that the mechanical vector nozzle can achieve high-precision control but has structural burdens, the fluidic thrust vectoring technology improves the response speed through the design of no moving parts but is accompanied by the loss of thrust, and the distributed electric propulsion system improves the hovering efficiency compared with the traditional helicopter. Addressing multi-physics coupling and non-linear control challenges in unmanned aerial vehicles, this paper elucidates the disturbance compensation advantages of self-disturbance rejection control technology and the optimal path generation capabilities of an enhanced path planning algorithm. These two approaches offer complementary technical benefits: the former ensures stable flight attitude, while the latter optimises flight trajectory efficiency. Through case studies such as the Skate demonstrator, the practical value of these technologies in enhancing UAV manoeuvrability and adaptability is further demonstrated. However, thermal management in extreme environments, energy efficiency and lack of standards are still bottlenecks in engineering. In the future, breakthroughs in high-temperature-resistant materials and intelligent control architectures are needed to promote the development of UAVs towards ultra-autonomous operation. This paper provides a systematic reference for the theory and application of thrust vectoring technology. Full article

The pea aphid, Acyrthosiphon pisum, possesses horizontally acquired fungal carotenoid biosynthesis genes, enabling de novo production of carotenoids. Although carotenoids are known to contribute to photo-protection and coloration, their potential role in energy metabolism and population fitness under thermal stress is still unclear. This study investigated the interactive effects of temperature and light intensity on energy homeostasis and life-history traits in A. pisum. Using controlled environmental regimes, we demonstrate that light intensity significantly influenced the ATP content, development, and reproductive output of A. pisum at 12 °C, but not at 22 °C. Under cold stress (12 °C), high light intensity (5000 lux) increased ATP content by 240%, shortened the pre-reproductive period by 46%, extended reproductive duration by 62%, and enhanced the net reproductive rate (R₀) and intrinsic rate of increase (rₘ) compared to low light intensity (200 lux). These effects were abolished at the optimal temperature (22 °C), indicating a temperature-gated, light-dependent mechanism. Demographic analyses revealed that carotenoid-associated solar energy harvesting significantly improves fitness under cold conditions, likely compensating for metabolic depression. Our findings reveal a novel ecological adaptation in aphids, where horizontally transferred genes may enable light-driven energy supplementation during thermal stress. This study provides new insights into the physiological mechanisms underlying insect resilience to climate variability and highlights the importance of light as a key environmental factor in shaping life-history strategies in temperate agroecosystems. Full article

Escherichia coli displays strong adaptability for growth and reproduction at low temperatures, with ribosome biogenesis being a critical process for its growth in cold environments. The cold-shock proteins (CSPs) encompass a protein family that can assist bacterial growth at low temperatures by acting as molecular chaperones. In this study, we investigated whether CSP CspA, CspE, and CspI affect ribosomal RNA (rRNA) transcription. Deletion of the single genes encoding these proteins had only a very marginal effect on cellular growth at low temperatures, and rRNA synthesis was hardly affected. Double and triple deletion of the genes encoding these proteins resulted in a much stronger phenotype providing evidence that CspA, CspE, and CspI play an essential role in maintaining 16S rRNA synthesis and enabling optimal cellular growth at low temperatures. These findings suggest the existence of efficient backup mechanisms able to compensate for the absence of a single CSP. Full article

Structured Light LiDAR is susceptible to lens scattering and temperature fluctuations, resulting in some level of distortion in the captured point cloud image. To address this problem, this paper proposes a high-performance 3D point cloud Least Mean Square filter based on Decision Tree, which is called the D−LMS filter for short. The D−LMS filter is an adaptive filtering compensation algorithm based on decision tree, which can effectively distinguish the signal region from the distorted region, thus optimizing the distortion of the point cloud image and improving the accuracy of the point cloud image. The experimental results clearly demonstrate that our proposed D−LMS filtering algorithm significantly improves accuracy by optimizing distorted areas. Compared with the 3D point cloud least mean square filter based on SVM, the accuracy of the proposed D−LMS filtering algorithm is improved from 86.17% to 92.38%, the training time is reduced by 1317 times and the testing time is reduced by 1208 times. Full article

In order to solve the problem of the efficiency reduction and complex manufacturing of traditional grating couplers under environmental temperature fluctuations, a Si₃N₄ high-efficiency grating coupler integrating a distributed Bragg reflector (DBR) and thermo-optical tuning layer is proposed. In this paper, the double-layer DBR is used to make the down-scattered light interfere with other light and reflect it back into the waveguide. The finite difference time domain (FDTD) method is used to simulate and optimize the key parameters such as grating period, duty cycle, incident angle and cladding thickness, achieving a coupling efficiency of −1.59 dB and a 3 dB bandwidth of 106 nm. In order to further enhance the temperature stability, the amorphous silicon (a-Si) thermo-optical material layer and titanium metal serpentine heater are embedded in the DBR. The reduction in coupling efficiency caused by fluctuations in environmental temperature is compensated via local temperature control. The simulation results show that within the wide temperature range from −55 °C to 150 °C, the compensated coupling efficiency fluctuation is less than 0.02 dB, and the center wavelength undergoes a blue shift. This design is compatible with complementary metal-oxide-semiconductor (CMOS) processes, which not only simplifies the fabrication process but also significantly improves device stability over a wide temperature range. This provides a feasible and efficient coupling solution for photonic integrated chips in non-temperature-controlled environments, such as optical communications, data centers, and automotive systems. Full article

A precision bandgap reference (BGR) is an essential building block in modern analog and mixed-signal systems, as it provides stable and predictable current and voltage references required for reliable operation across process, voltage, and temperature variations. However, one of the key challenges in conventional BGR circuits is their sensitivity to resistance variations, which directly impacts the accuracy of bias currents. Even small changes in resistance can lead to significant current mismatch between the core branches of the circuit, thereby degrading output stability and limiting the precision of the overall system. This degradation is particularly problematic in high-performance applications such as data converters, oscillators, and low-power biasing networks, where robust current matching is critical. To address this limitation, this work proposes a resistance-compensated BGR architecture that incorporates an auxiliary trimming network and a compensation branch. The trimming network senses variations in resistance and generates a control bias proportional to the deviation, while the compensation branch injects a corrective current into the output stage. By dynamically balancing the mismatch introduced by resistor spread, the proposed architecture effectively restores current stability across process corners. This method achieves reduction in the current variation across resistance corners from 21% to 3% in worst-case corners (±3%). This approach offers enhancement of current mismatches in analog systems in which robust current is essential. Full article