Search Results (638)

Electro-permanent magnet (EPM) technology is characterized by high integration, strong modularity, and stable magnetic force, making it a current research focus when combined with sheet metal deep drawing processes to develop EPM blank holder deep drawing technology. In this study, we investigated the issue of thermal magnetic quantitative magnetic loss after the prolonged use of the EPMBH process, analyzing the variation in magnetic force with the temperature increase to provide necessary data support for the application of the EPMBH. First, a thermal network model for the four-magnetic pole unit EPM magnetic device was established, and through calculations on this model, the thermal equilibrium temperatures for the permanent magnet (PM)-NdFeB and reversible magnet (RM)-AlNiCo were found to be 72.13 °C and 72.41 °C, respectively. Second, the magnetic performance of PM and RM at different temperature points was measured to analyze the variation in their magnetic characteristics with the temperature increase. Third, a magnetic force model of the EPM magnetic device was established, and finite element analysis was conducted using the measured magnetic characteristics data of RM and PM. The results indicated that an increase in temperature leads to a reduction in magnetic force, with a maximum reduction of 18.57% observed after thermal equilibrium. An experimental testing platform was designed and built to validate the calculation and simulation results. Finally, a sheet metal deep drawing experiment using the EPMBH process was conducted, taking into account thermal magnetic loss factors. The results showed that magnetic force loss due to temperature rise affects the forming quality of the sheet metal. Therefore, in practical applications, it is necessary to establish a real-time temperature monitoring system and develop a temperature-based magnetic force compensation module. Full article

This research demonstrates the possibility and expediency of forming local electric energy systems (LEESs) based on renewable sources of energy (RSE) as balancing groups in the electric power system (EPS), which can maintain efficiency and provide power supply to consumers in an autonomous mode. The LEES is a part of the EPS of thermal and nuclear power plants and is considered as a separate balancing group. LEESs are designed in such a way that they can operate autonomously in both normal and extreme conditions in the EPS. The sources of electricity in LEESs are small hydroelectric power plants (SHPPs), photovoltaic power plants (PVPPs), and wind power plants (WPPs), whose electricity generation is unstable due to dependence on natural conditions. Therefore, the structure of a LEES with RSE includes an energy storage system with reserves sufficient to compensate for the unstable generation and balancing of the mode. LEESs can differ significantly in terms of key technical and economic indicators (power supply reliability, power losses, and power quality), and therefore, it is necessary to choose the optimal one. It is not advisable to optimize the quality of power supply in a LEES by individual indicators, as improvement of one indicator may lead to deterioration of another. The functional readiness of a LEES should be assessed by the quality of operation, which depends on reliability, power losses, and power quality. To simplify the task of assessing the quality of operation, which is a vector optimization problem, a method for determining the integral indicator as a number that characterizes the LEES and reflects the compromise between the values of reliability, power losses, and power quality has been developed. The integral indicator of the functioning of complex systems is based on a combination of the theory of Markov processes and the criterion method of similarity theory. The value of the integral indicator of the quality of operation of the LEES allows for comparing different variants of power transmission and distribution systems without determining individual components of technical and economic indicators—reliability, power losses, and power quality. The offered integral indicator of the quality of functioning of a LEES with RSE corresponds to the general requirements for such indicators. It reflects the actual operating conditions; allows for assessing the efficiency, quality, and optimality of power supply systems; and can be easily decomposed into partial indicators. Full article

This study analyzes the performance of thermal energy storage tanks and chillers in efficiently operating cooling systems for smart greenhouses in hot, arid climates such as the United Arab Emirates (UAE). The performance of chillers is heavily influenced by outdoor air temperatures, with the coefficient of performance (COP) of chillers decreasing and energy consumption increasing as daytime temperatures rise. This study found that when the outdoor air temperature reached 46.6 °C, the COP of the chiller dropped to 2.18, representing a 24.6% decrease compared to the COP of 2.89 at 35 °C. Conversely, at night, when the outdoor air temperature dropped to 28.3 °C, the chiller’s performance recovered, with the COP rising to 3.67. To address this, a strategy utilizing thermal energy storage tanks to store chilled water at night for use during the day was proposed, compensating for the decline in chiller performance. The results showed that when the thermal energy storage capacity was set at 40%, energy consumption decreased by up to 15%. However, while increasing the thermal energy storage capacity beyond 50% effectively reduced the peak load on the chiller, further increasing it beyond 60% led to a rise in chiller capacity and energy consumption. Therefore, this study concludes that setting the thermal energy storage capacity to no more than 50% is the most effective strategy to maximize chiller performance and reduce energy consumption. These findings provide crucial guidelines for the design and operation of cooling systems, offering valuable strategies to optimize the operation of smart greenhouses in hot climates. Full article

Thermal insulation materials are important for building energy conservation, but the inherent combustibility of these materials increases the fire risk of building facades. To better understand the fire behaviors of these materials, the study of the kinetics of thermal insulation pyrolysis is particularly important because it is the initial step in ignition and combustion during fire. In this paper, the pyrolysis behavior of expanded polystyrene (EPS), a typical non-charring insulation polymer, has been investigated by thermogravimetric analysis at five different heating rates. The model-free kinetic analysis showed that the obtained average values for E and lnA were 151.23 kJ/mol and 21.29 ln/s, respectively. Model-fitting CR and masterplot methods indicated that f(α) = [2(1-α)[-ln(1-α)]]^1/2 is considered the pyrolysis reaction mechanism of EPS degradation. Based on these results, the equation of the kinetic compensation effect was further developed as lnA = −3.1955 + 0.1736 E_α. Finally, the reaction model was reconstructed with the result of the expression f(α) = 3.95335α^0.24174 (1-α) [-ln(1-α)]^1.64712. In addition, PY-GC-MS experiments were conducted to analyze the composition of EPS pyrolysis volatiles. The results showed that the products were mainly compounds of benzene, naphthalene, and biphenyl. The analysis of EPS pyrolysis behavior and evolved gas provides numerical guidance for the future treatment and fire protection of insulation materials. Full article

In response to the increasingly strict performance requirements of large molds, a novel Cr-Mo-V hot-work die steel has been developed. In order to study the high-temperature hot deformation behavior and plasticity of the novel steel, hot compression tests were conducted on the Gleeble-1500D thermal simulation testing machine at a deformation temperature of 950~1200 °C and a strain rate of 0.001~5 s⁻¹. Based on the Arrhenius constitutive model, a novel Cr-Mo-V steel high-temperature constitutive model considering strain was established. The reliability and applicability of this modified model, which includes strain compensation, were assessed using the phase relationship coefficient (R) and the average absolute relative error (AARE). The values of R and AARE for comparing predicted outcomes with experimental data were 0.98902 and 3.21%, respectively, indicating that the model demonstrated high precision and reliability. Based on the Prasad criterion, a 3D hot processing map of the novel Cr-Mo-V steel was established, and the instability zone of the material was determined through the hot processing map: the deformation temperature (950~1050 °C) and strain rate (0.001~0.01 s⁻¹) were prone to adiabatic shear and crystal mixing. The suitable processing range was determined based on the hot processing map: The first suitable processing area was the strain range of 0.05~0.35, the temperature range was 1100~1175 °C, and the strain rate was 0.001~0.009 s⁻¹. The second suitable processing area was a strain of 0.45~0.65, a temperature of 1100~1200 °C, and a strain rate of 0.0024~0.33 s⁻¹. Finally, the forging process of hundred-ton die steel forging was developed by combining 3D hot processing maps with finite element simulation, and the forging trial production of 183 t forging was carried out. The good forging quality indicated that the established hot processing map had a good guiding effect on the production of 100-ton test steel forging. Full article

We investigated the carrier dynamics of ammonothermal Mn-compensated gallium nitride (GaN:Mn) semiconductors by using sub-bandgap and above-bandgap photo-excitation in a photoluminescence analysis and pump–probe measurements. The contactless probing methods elucidated their versatility for the complex analysis of defects in GaN:Mn crystals. The impurities of Mn were found to show photoconductivity and absorption bands starting at the 700 nm wavelength threshold and a broad peak located at 800 nm. Here, we determined the impact of Mn-induced states and Mg acceptors on the relaxation rates of charge carriers in GaN:Mn based on a photoluminescence analysis and pump–probe measurements. The electrons in the conduction band tails were found to be responsible for both the photoconductivity and yellow luminescence decays. The slower red luminescence and pump–probe decays were dominated by Mg acceptors. After photo-excitation, the electrons and holes were quickly thermalized to the conduction band tails and Mg acceptors, respectively. The yellow photoluminescence decays exhibited a 1 ns decay time at low laser excitations, whereas, at the highest ones, it increased up to 7 ns due to the saturation of the nonradiative defects, resembling the photoconductivity lifetime dependence. The fast photo-carrier decay time observed in ammonothermal GaN:Mn is of critical importance in high-frequency and high-voltage device applications. Full article

Energy is an important aspect concerning global economic development and environmental conservation. Economic growth has been accompanied by extensive use of fossil fuels, resulting in significant emissions of greenhouse gases and other pollutants. Therefore, researchers have turned their attention to low/zero carbon fuels. Among these, biofuels have attracted wide attention due to their relatively low cost, clean combustion products and renewability. This article reviews the combustion, performance and emission characteristics of internal combustion (IC) engines fueled with biofuels categorized into three generations by their raw material sources. According to most research findings, biofuels generally exhibit poorer combustion performance in IC engines compared to fossil fuels due to their high viscosity and low lower heating value. However, these biofuels, characterized by a high oxygen content, facilitate more complete combustion and reduce emissions of CO, UHC and smoke, albeit increasing NO_x emission and fuel consumption. Both thermal efficiency and brake power also tend to decrease, but various optimization strategies such as advanced combustion modes or injection control methods can partially compensate for these drawbacks. In conclusion, biofuels should be a promising low-carbon fuel for IC engines in the future. Full article

A space-borne telescope is used for Earth observation at about 500 km above sea level in the thermosphere where the air density is very low and the temperature increases significantly during daytime. If the telescopes are aligned and characterized on the ground with standard temperature and pressure (STP) conditions, different from that of the thermosphere, their performance could drift during their mission. Therefore, they are usually placed in a thermal vacuum chamber during ground testing in order to verify the system can perform well and withstand the harsh environment such as a high vacuum level and large temperature variations before being launched. Nevertheless, it remains a challenge to build up an in situ optical measurement system for a large aperture telescope in a thermal vacuum chamber due to the finite internal space of the chamber, limited aperture size of the vacuum view port and thermal dissipation problem of the measuring instruments. In this paper, a novel architecture of an interferometer whose light path travels across a vacuum chamber and an atmospheric environment has been proposed to resolve all of these technical issues. The major feature of the architecture is the diverger lens being located within the vacuum chamber, leaving the rest of the interferometer outside. The variation of the interference fringe due to the relocation of the diverger lens has been investigated with optical simulations and the solutions for compensation have also been proposed. Together with a specific alignment procedure for the proposed architecture, the interferogram has been successfully acquired from a prototype testbed. Full article

Home-built equipment will be presented able to measure the thermal expansion (with a flat indenter) and indentation depth (with a pointed indenter) up to 1100 °C. In dilatometer mode, the allotropic phase transformations can be studied. For hardness, a Rockwell-type measurement is adopted. First, we apply a small load and measure the displacement consisting of a dominant positive thermal expansion and a small negative indentation depth contribution. Then, we repeat the thermal cycle with such a high load that the compensation appears at around 250–300 °C. With increasing temperature, the indentation depth starts to dominate and we can notice a contraction. The indentation depth as a function of temperature, ID(T), will be obtained by subtracting the high load curve from the low load curve. A new rational fraction expression will be tested to describe the thermal softening of pure metals and refractory HEAs. Still, we are working on improving the equipment to extend the working temperature up to 1200 °C. Full article

The scale factor of thermal sensitivity serves as a crucial performance metric for micro-electromechanical system (MEMS) gyroscopes, and is commonly employed to assess the temperature stability of inertial sensors. To improve the temperature stability of the scale factor of MEMS gyroscopes, a self-compensation method is proposed. This is achieved by integrating the primary and secondary relevant parameters of the scale factor using the partial least squares regression (PLSR) algorithm. In this paper, a scale factor prediction model is presented. The model indicates that the resonant frequency and demodulation phase angle are the primary correlation terms of the scale factor, while the drive control voltage and quadrature feedback voltage are the secondary correlation terms of the scale factor. By employing a weighted fusion of correlated terms through PLSR, the scale factor for temperature sensitivity is markedly enhanced by leveraging the predicted results to compensate for the output. The results indicate that the maximum error of the predicted scale factor is 0.124% within the temperature range of −40 °C to 60 °C, and the temperature sensitivity of the scale factor decreases from 6180 ppm/°C to 9.39 ppm/°C. Full article

Femtosecond laser processing combines highly accurate structuring with low residual heating of materials, low thermal damage, and nonlinear absorption processes, making it suitable for the machining of transparent brittle materials. However, with high average powers and laser pulse repetition rates, residual heating becomes relevant. Here, we present a study of the femtosecond laser pulse-on-demand operation regime, combined with regular scanners, aiming to improve throughput and quality of processing regardless of the scanner’s capabilities. We developed two methods to define the needed pulse-on-demand trigger sequences that compensate for the initial accelerating scanner movements. The effects of pulse-on-demand operation were studied in detail using direct process monitoring with a fast thermal camera and indirect process monitoring with optical and topographical surface imaging of final structures, both showing clear advantages of pulse-on-demand operation in precision, thermal effects, and structure shape control. The ability to compensate for irregular scanner movement is the basis for simplified, cheaper, and faster femtosecond laser processing of brittle and heat-susceptible materials. Full article

Integrating multiple types of sensors into autonomous systems, such as cars and robots, has become a widely adopted approach in modern technology. Among these sensors, RGB cameras, thermal cameras, and LiDAR are particularly valued for their ability to provide comprehensive environmental data. However, despite their advantages, current research primarily focuses on the one or combination of two sensors at a time. The full potential of utilizing all three sensors is often neglected. One key challenge is the ego-motion compensation of data in dynamic situations, which results from the rotational nature of the LiDAR sensor, and the blind spots of standard cameras due to their limited field of view. To resolve this problem, this paper proposes a novel method for the simultaneous registration of LiDAR, panoramic RGB cameras, and panoramic thermal cameras in dynamic environments without the need for calibration targets. Initially, essential features from RGB images, thermal data, and LiDAR point clouds are extracted through a novel method, designed to capture significant raw data characteristics. These extracted features then serve as a foundation for ego-motion compensation, optimizing the initial dataset. Subsequently, the raw features can be further refined to enhance calibration accuracy, achieving more precise alignment results. The results of the paper demonstrate the effectiveness of this approach in enhancing multiple sensor calibration compared to other ways. In the case of a high speed of around 9 m/s, some situations can improve the accuracy about 30 percent higher for LiDAR and Camera calibration. The proposed method has the potential to significantly improve the reliability and accuracy of autonomous systems in real-world scenarios, particularly under challenging environmental conditions. Full article

Pervious concrete, because of its high porosity, is a suitable material for reducing the effects of water precipitations and is primarily utilized in road pavements. In this study, the effects of binder-to-aggregate (B/A) ratios, as well as mineral admixtures with and without polypropylene fibers (PPFs) (0.2% by volume), including fly ash (FA) or silica fume (SF) (10% by substitution of cement), on the mechanical properties and durability of pervious concrete were experimentally observed. The experimental campaign included the following tests: permeability, porosity, compressive strength, splitting tensile strength, and flexural strength tests. The durability performance was evaluated by observing freeze–thaw cycles and abrasion resistance after 28 d curing. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), thermal analysis (TGA-DTA), and scanning electron microscopy (SEM) combined with energy dispersive spectroscopy (EDS) were employed to investigate the phase composition and microstructure. The results revealed that, for an assigned B/A ratio identified as optimal, the incorporation of mineral admixtures and fibers mutually compensated for their respective negative effects, resulting in the effective enhancement of both mechanical/microstructural characteristics and durability properties. In general, pervious concrete developed with fly ash or silica fume achieved higher compressive strength (>35 MPA) and permeability of 4 mm/s, whereas the binary combination of fly ash or silica fume with 0.2% PPFs yielded a flexural strength greater than 6 MPA and a permeability of 6 mm/s. Silica fume-based pervious concrete exhibited excellent performance in terms of freeze–thaw (F-T) cycling and abrasion resistance, followed by fiber-reinforced pervious concrete, except fly ash-based pervious concrete. Microstructural analysis showed that the inclusion of fly ash or silica fume reduced the harmful capillary pores and refined the pore enlargement caused by PPFs in the cement interface matrix through micro-filling and a pozzolanic reaction, leading to improved mechanical and durability characteristics of pervious concrete. Full article

This paper introduces a methodology to compensate inertial Micro-Electro-Mechanical System (IMU-MEMS) time-varying calibration loss, induced by stress and aging. The approach relies on a periodic assessment of the sensor through specific stimuli, producing outputs which are compared with the response of a high-precision sensor, used as ground truth. At any re-calibration iteration, differences with respect to the ground truth are approximated by quantization-aware trained tiny neural networks, allowing calibration-loss compensations. Due to the unavailability of aging IMU-MEMS datasets, a synthetic dataset has been produced, taking into account aging effects with both linear and nonlinear calibration loss. Also, field-collected data in conditions of thermal stress have been used. A model relying on Dense and 1D Convolution layers was devised and compensated for an average of 1.97 g and a variance of 1.07 g², with only 903 represented with 16 bit parameters. The proposed model can be executed on an intelligent signal processing inertial sensor in 126.4 ms. This work represents a step forward toward in-sensor machine learning computing through integrating the computing capabilities into the sensor package that hosts the accelerometer and gyroscope sensing elements. Full article

To boost the sustainable development of energy and the environment, a new power system with clean energy sources has been proposed by the Chinese government and traditional coal-fired power units are being transformed into regulation service providers for this new energy power system. Then, in this study, complementary power generation cooperation between traditional coal-fired power and new energy power producers is analyzed and discussed, and the energy quota agents, power sellers, are also included. Based on the cooperation game idea, different decision-making models of the tripartite power entities are elaborately constructed. Then, according to the price linkage mechanism between new energy and traditional thermal power, the profit of all power subjects is calculated and the profit allocation process is also analyzed. The conclusions show that the similarity of the two wholesale power price coefficients verifies the symmetry of the cooperative status of power producers. For BPC and SPC quota patterns, for example, BPC is bundled with new energy power and green certificates, whereas SPC is separate. Under the SPC pattern, there is a critical value for effective cooperation between the two power producers in the price range of traditional thermal power or new energy, which can achieve a win–win situation of increasing economic benefits and the consumption scale. Under the BPC pattern, the dynamic benefit compensation mechanism, which is the corrected Shapley value based on the RPS quota ratio, can solve the compressed profit of traditional coal-fired power producers. In contrast, the overall effect of profit allocation using the nucleolar method is not ideal. This study aims to give full play to the elastic induction effect of RPS to promote the sustainable transformation of traditional thermal power energy, especially combining the market mechanism to encourage traditional coal-fired power units to improve green technology to advance the construction of the green power market in China. Full article