In this paper, a series of models were established, and based on the Google Flu Trends (GFT) data and Centers for Disease Control (CDC) data. The models include the GFT regression model (model 1), weighted GFT regression model (model 2), GFT+CDC regression model (model 3), CDC regression model (model 4), and weighted CDC regression model (model 5). All models were utilized to predict and assess influenza activity across ten regions of the United States. The Least Squares (LS) and back-propagation neural network based on the genetic algorithm (GA-BP) are used to fit the model parameters, and the error and historical sample fitting accuracy of each model are compared. The results show that models 4 and 5 are superior to other models. To optimize the prediction model, the seasonal characteristics of influenza incidence were investigated, and flu-prediction models for the high-flu season and low-flu season were established. The experimental results show that the prediction model of seasonal influenza is superior to the non-seasonal model. The influenza-like illness (ILI) values predicted by the seasonal flu model are consistent with information provided by the CDC, suggesting that the results accurately reflect influenzaepidemic characteristics and can thus be readily applied for the prevention and control of influenza.

The use of plasma sources is becoming increasingly prominent in fields such as plasma physics, materials processing, and environmental engineering. However, accurately measuring the internal temperature of plasma sources remains a challenging task. An ultrasonic temperature measurement system was designed in this study using an Al ₂ O ₃ crystal rod as the propagation medium for a waveguide sensor. Temperature tests were conducted within an inductively coupled plasma radio frequency-coupled plasma source. Experimental results demonstrated that the sensor can operate stably in harsh plasma environments. The maximum temperature reached 1966°C with varying pressure and fixed plasma source output power. With fixed internal plasma source pressure and varying output power, the maximum temperature reached 1800°C. These results not only hold significant theoretical and practical value but also represent a new direction for applying ultrasonic high-temperature measurement systems in harsh environments.

In extremely harsh high-temperature environments in aerospace, industrial manufacturing and other fields, traditional ultrasonic temperature measurement technology has certain limitations. This paper proposes a differential single crystal sapphire ultrasonic temperature measurement method based on the magnetostrictive effect. This method abandons the traditional sensitive flexural structure and uses two single-crystal sapphire waveguides of the same material, same diameter, and slightly different lengths as sensing elements. By measuring the time delay difference between their end-face echoes, the sound velocity is inverted and the temperature is measured. COMSOL multi-physics v6.1 simulation was used to optimize the bias magnetic field design of the magnetostrictive transducer, which improved the system’s energy conversion efficiency and high-temperature stability. Experimental results show that in the range of 300–1200 °C, the sensor delay increases monotonically with increasing temperature, the sound speed shows a downward trend, and the repeatability error is less than 5%; the differential processing method effectively suppresses common mode noise in the range of 300–700 °C, and still shows high sensitivity above 800 °C. This research offers a technical solution with high reliability and accuracy for temperature monitoring in extreme environments such as those characterized by high temperatures and high pressures.

To improve dynamic thermal measurement accuracy on aero-engine hot-section components, integrated heat flux/temperature thin-film sensors (TFHFs) were fabricated using micro-nano technology. This study simulated and compared the time constant calibration of the TFHFs’ temperature component under step laser heating and step furnace heating, demonstrating the necessity of power feedback control in laser-based dynamic calibration. Factors influencing the dynamic response of the heat flux component under both radiation and convection were also analyzed. A laser-based test platform with constant-temperature feedback control was developed to validate the simulations. Tests revealed that overshoot in the heat flux response originates from non-ideal longitudinal heat transfer, while the feedback control reduced the temperature time constant by at least half (At the 1000 °C step steady state, the time constant decreased from 2 s to 0.85 s), overcoming the challenge of inaccurate calibration due to non-steady conditions. High-speed wind tunnel tests under convective conditions confirmed that the dynamic response of TFHFs is predominantly influenced by flow velocity. The study enables accurate dynamic measurement of composite thermal parameters under varied thermal boundaries.

Compared to traditional temperature measurement methods, ultrasonic temperature measurement technology based on the principle of resonance offers advantages such as shorter section lengths, higher signal amplitude, and reduced signal attenuation. First, the type of sensor-sensitive element was determined, with a resonant design chosen to improve measurement performance; using magnetostrictive and resonant temperature measurement principles, the length, diameter, and resonator dimensions of the waveguide rod were designed, and a molybdenum–rhenium alloy (Mo-5%Re) material suitable for high-temperature environments was selected; COMSOL finite element simulation was used to simulate the propagation characteristics of acoustic signals in the waveguide rod, observing the distribution of sound pressure and energy attenuation, verifying the applicability of the model in high-temperature testing environments. Second, a resonant temperature sensor consistent with the simulation parameters was prepared using a molybdenum–rhenium alloy waveguide rod, and an ultrasonic resonant temperature-sensing system suitable for high-temperature environments up to 1800 °C was constructed using the molybdenum–rhenium alloy waveguide rod. The experiment used a tungsten–rhenium calibration furnace to perform static calibration of the sensor. The temperature range was set from room temperature to 1800 °C, with the temperature increased by 100 °C at a time, and it was maintained at each temperature point for 5 to 10 min to ensure thermal stability. This was conducted to verify the performance of the sensor and obtain the functional relationship between temperature and resonance frequency. Experimental results show that during the heating process, the average resonance frequency of the sensor decreased from 341.8 kHz to 310.37 kHz, with an average sensitivity of 17.66 Hz/°C. During the cooling process, the frequency increased from 309 kHz to 341.8 kHz, with an average sensitivity of 18.43 Hz/°C. After cooling to room temperature, the sensor’s resonant frequency returned to its initial value of 341.8 kHz, demonstrating excellent repeatability and thermal stability. This provides a reliable technical foundation for its application in actual high-temperature environments.