Precise Temperature Control Research Articles

780 nm Narrow Linewidth External Cavity Diode Laser for Quantum Sensing

To meet the demands of laser communication, quantum precision measurement, cold atom technology, and other fields for narrow linewidth and low-noise light sources, an external cavity diode laser (ECDL) operating in the wavelength range around 780 nm was set up with a Fabry–Pérot etalon (F–P) and an interference filter (IF) in the experiment. The interference filter type ECDL (IF–ECDL) with butterfly-style packaging configuration has continuous wavelength tuning within a specified range through precise temperature and current control and has excellent single-mode characteristics. Experimental results indicate that the output power of the IF–ECDL is 14 mW, with a side-mode suppression ratio (SMSR) of 54 dB, a temperature-controlled mode-hop-free tuning range of 527 GHz (1.068 nm), and an output linewidth of 570 Hz. Compared to traditional lasers operating at 780 nm, the IF–ECDL exhibits narrower linewidth, lower noise, and higher spectral purity, and its dimensions are merely 25 × 15 × 8.5 mm3 weighing only 19.8 g, showcasing remarkable miniaturization and lightweight advantages over similar products in current research fields.

Development and evaluation of a precision heat treatment device for delaying postharvest softening of muskmelon

To extend the limited commercial storage of muskmelons due to insufficient shelf life, a heat treatment device with precise temperature control was designed and applied to three muskmelon varieties: "Xizhou Mi 25" (XZM), "Jinmi 3" (JM), and "Jiashi" (JS). The effectiveness of this device and the effect of heat treatment on the softening of muskmelons during storage were evaluated. The results indicated no significant difference between the temperatures set by the control system and the actual measured temperatures (p > 0.05), demonstrating the high accuracy of the temperature control system. After optimization of the heat treatment device, no thermal damage was observed in the heat-treated group of muskmelons. The energy consumption of the heat treatment device was only half that of the insulated tank. By the 18th day of storage, the protopectin (PP) content in the heat-treated group was significantly lower than in the control group. Correlation analysis showed that hardness was positively correlated with PP content and negatively correlated with water-soluble pectin (WSP). Additionally, cell wall metabolism-related enzyme activities were negatively correlated with PP content. These results indicated that the heat treatment effectively delayed muskmelon softening during postharvest storage. This study provides technical support for the industrial application of heat treatment devices in muskmelon preservation.

Machine learning in additive manufacturing——NiTi alloy’s transformation behavior

The laser powder bed fused NiTi alloys (LPBF-NiTi) demonstrate shape memory functionality and superelasticity as a result of their distinctive phase transition characteristics. Nevertheless, achieving precise control and regulation of the phase transition temperature poses a challenge, influenced by factors like powder composition and process parameter. In this study, a feature screening strategy and machine learning (ML) method were employed to predict and regulate the phase transition temperature of LPBF-NiTi alloy, offering a more efficient and cost-effective alternative to traditional experimental methods of regulation and control. Specifically, accuracy analysis was performed on LPBF-NiTi phase transition datasets with varying compositions and process conditions utilizing generalized regression neural network (GRNN), and other methods. The findings indicate that the interpretable features extracted through the selection strategy outlined in this study when combined with the GRNN model, demonstrate a high level of prediction accuracy (R2 = 0.97). To investigate the accuracy of the model, this study utilized various process parameters to fabricate NiTi alloys with different compositions from Ni50.8Ti49.2 alloy powder. Using this model, the study identified a novel, larger window of optimal LPBF processing that allows for controllable complex phase transitions.

A Safe Fiber-Optic-Sensor-Assisted Industrial Microwave-Heating System.

Industrial microwave-heating systems are pivotal in various sectors, including food processing and materials manufacturing, where precise temperature control and safety are critical. Conventional systems often struggle with uneven heat distribution and high fire risks due to the intrinsic properties of microwave heating. In this work, a fiber-optic-sensor-assisted monitoring system is presented to tackle the pressing challenges associated with uneven heating and fire hazards in industrial microwave systems. The core innovation lies in the development of a sophisticated fiber-optic 2D temperature distribution sensor and a dedicated fire detector, both designed to significantly mitigate risks and optimize the heating process. Experimental results set the stage for future innovations that could transform the landscape of industrial heating technologies toward better process quality.

Thermal transportation of radiative cathode nanotube‐based nanofluid on a stretching/shrinking wedge with varying magnetism and heat source

AbstractThe complex heat transfer processes occurring in a magnetized water‐based hybrid nanofluid flowing past a stretching or shrinking wedge are investigated in this work. The research highlights the significant influence of the wedge angle on fluid flow patterns and temperature gradients, emphasizing how larger angles cause changes in pressure, flow separation, and temperature profiles. Additionally, the study emphasizes the importance of radiation effects near surfaces, where increased radiation often leads to cooling due to thermal energy emission. The findings have implications in industries such as aerospace, electronics, thermal management, and groundwater resources management where precise temperature control is critical for safe and efficient operations. The numerical method applied to solve the governing equations in the study is the fourth‐order Runge–Kutta technique with shooting technique. This method efficiently solves the boundary value problem by converting it into a system of first‐order initial value problems. Then shooting technique is used to solve the system, starting with an adequate initial guess. The study's results are presented in tabular and graphical forms, providing valuable insights into the complex fluid dynamics and thermal behavior in the given setting, enabling more informed decision‐making and optimization in relevant engineering applications. Increased radiation frequently results in a cooling effect owing to thermal energy output. Heat sinks/heat sources are crucial in temperature regulation and are effective in lowering temperatures via processes. We also emphasize the importance of radiation impacts near surfaces, where increased radiation frequently leads to cooling owing to thermal energy emission. The numerical values of skin friction and Nusselt number for various parameters in the cases of shrinking and stretching provide crucial insights into the heat transmission and frictional properties of the system under examination. These quantitative results contribute to a better understanding of the complex fluid dynamics and thermal behavior in the given setting, emphasizing the significance of the research findings.

Design and evaluation of an active vineyard heating system to simulate temperature increase in the context of climate change

The current study introduces an innovative direct and active heating system designed for precise temperature control in vineyards. This system serves as a valuable tool for investigating the influence of climate change on grapevine physiology and, consequently, the characteristics of the resulting wine. The research took place in an experimental vineyard located in Mendoza, Argentina, with V. vinifera cvs. trained to a vertical shoot positioning trellis system over two consecutive growing seasons. The system design utilized electric hot water tanks and polypropylene pipes attached to the foliage catch wires. Over two growing seasons, the system consistently elevated the ambient air temperatures within the canopy by 2.5 ± 0.12 °C compared to the control group. This temperature increase emulated the temperature projections for Mendoza as forecasted by the IPCC by the end of this century. The system displayed heating uniformity, as evidenced by the absence of both vertical and horizontal temperature gradients. Additionally, the significant variation in mean daytime and night-time temperatures between the control and heated treatments highlighted the effectiveness of the system in modifying temperature conditions on a diurnal basis. The heated treatment applied with this system proved to have an effective biological impact on the physiology of grapevines. In both seasons, plants under the heated treatment advanced their bud break and harvest dates. The study showed a significant growth enhancement in the heated treatment, with apical shoots extending significantly longer than those in the control treatment. Additionally, the total soluble solids content increased in the heating treatment, while yield decreased, for both experimental seasons. These results illustrate the robust performance of the system throughout the entire growth period, regardless of fluctuations in atmospheric conditions. This study establishes a new foundation for future research on grapevine responses to climate change. It also opens the door to the implementation of effective adaptation strategies in vineyards, promising a more resilient and adaptable future for grape cultivation.

Modeling of the metal–insulator transition temperature in alio-valently doped VO2 through symbolic regression

The correlated semiconductor vanadium dioxide (VO2) exhibits an insulator–metal transition (IMT) near room temperature, which is of interest in various device applications. Precise IMT temperature control is crucial to determine the use cases across technologies such as thermochromic windows, actuators for robots or neuronal oscillators. Doping the cation or anion sites can modulate the IMT by several tens of degrees and control hysteresis. However, modeling the effects of control parameters (e.g., doping concentration, type of dopants) is challenging due to complex experimental procedures and limited data, hindering the use of traditional data-driven machine learning approaches. Symbolic regression (SR) can bridge this gap by identifying nonlinear expressions connecting key input parameters to target properties, even with small data sets. In this work, we develop SR models to capture the IMT trends in VO2 influenced by different dopant parameters. Using experimental data from the literature, our study reveals a dual nature of the IMT temperature with varying tungsten (W) doping concentrations. The symbolic model captures data trends and accounts for experimental variability, providing a complementary approach to first-principles calculations. Our feature-driven analysis across a broader class of dopants informs selectivity and provides qualitative insights into tuning phase transition properties valuable for neuromorphic computing and thermochromic windows.

Temperature correction of near-infrared spectra of raw milk

Accurate milk composition analysis is crucial for improving product quality, economic efficiency, and animal health in the dairy industry. Near-infrared (NIR) spectroscopy can quantify milk composition quickly and nondestructively. However, external factors, such as temperature fluctuations, can alter the molecular vibrations and hydrogen bonding in milk, altering the NIR spectra and leading to errors in predicting key constituents such as fat, protein, and lactose. This study compares the effectiveness of Piecewise Direct Standardization (PDS), Continuous PDS (CPDS), External Parameter Orthogonalization (EPO), and Dynamic Orthogonal Projection (DOP in correcting the impact of temperature-induced variations on predictions in milk long-wave NIR spectra (LW-NIR, 1000–1700 nm).A total of 270 raw milk samples were analyzed, collecting both reflectance and transmittance spectra at five different temperatures (20 °C, 25 °C, 30 °C, 35 °C, and 40 °C). The experimental setup ensured precise temperature control and accurate spectral measurements. PLSR models were calibrated at 30 °C to predict milk fat, protein, and lactose content. The performance of these models was assessed before and after applying the temperature correction methods, with a primary focus on reflectance spectra.Results indicate that EPO and DOP significantly enhance model robustness and prediction accuracy across all temperatures, outperforming PDS and CPDS, especially for lactose prediction. These orthogonalization methods were compared against PLSR models calibrated with spectra from all temperatures. EPO and DOP showed comparable or superior performance, highlighting their effectiveness without requiring extensive temperature-specific calibration data. These findings suggest that orthogonalization methods are particularly suitable for in-line milk quality measurements under farm conditions where temperature control is challenging. This study highlights the potential of advanced chemometric techniques to improve real-time, on-farm milk composition analysis, facilitating better farm management and enhanced dairy product quality.

Synthesis of Arrayed Tungsten Disulfide Nanotubes.

Tungsten disulfide nanotubes (WS2-NTs), with their cylindrical structure composed of rolled WS2 sheets, have attracted much interest because of their unique physical properties reflecting quasi-one-dimensional chiral structures. They exhibit a semiconducting electronic structure regardless of their chirality, and various semiconducting and optoelectronic device applications have been demonstrated. The development of techniques to fabricate arrayed WS2-NTs is crucial to realizing the highest device performance. Since the discovery of WS2-NTs, various synthesis techniques have been reported; however, horizontally arrayed WS2-NTs have never been successfully synthesized. Here, we demonstrate a simple technique to synthesize arrayed WS2-NTs. Through precise temperature and gas control, W18O49 nanowires are grown along the [1̅101] direction on an r-plane sapphire substrate, and the nanowires are converted into nanotubes via sulfurization under optimized conditions. The demonstrated synthesis technique for arrayed WS2-NTs will play a central role in the fabrication of devices using transition-metal dichalcogenide nanotubes.

A Data-Driven Online Prediction Model for Battery Charging Efficiency Accounting for Entropic Heat

This study proposes a charging efficiency calculation model based on an equivalent internal resistance framework. A data-driven neural network model is developed to predict the charging efficiency of lithium titanate (LTO) batteries for 5% state of charge (SOC) segments under various charging conditions. By considering the impact of entropy change on the open-circuit voltage (OCV) during the charging process, the accuracy of energy efficiency calculations is improved. Incorporating battery data under various charging conditions, and comparing the predictive accuracy and computational complexity of different hyperparameter configurations, we establish a backpropagation neural network model designed for implementation in embedded systems. The model predicts the energy efficiency of subsequent 5% SOC segments based on the current SOC and operating conditions. The results indicate that the model achieves a prediction error of only 0.29% under unknown charging conditions while also facilitating the deployment of the neural network model in embedded systems. In future applications, the relevant predictive data can be transmitted in real time to the cooling system for thermal generation forecasting and predictive control of battery systems, thereby enhancing temperature control precision and improving cooling system efficiency.

Liquid crystal-based temperature-controlled recirculating flat jet system.

In this paper, the design and implementation of a temperature-controlled recirculating flat jet system for liquid crystals (LCs)-based experiments are presented. In these experiments, the target liquid is usually exposed to medium to high laser fluences, possibly resonant with specific excitation, thus resulting in a change of local temperature and sudden degradation. To overcome this problem, each laser pulse must interact with a new volume of liquid, preferably with flat surfaces, while avoiding the use of substrates. A well-established solution consists of impinging two identical laminar jets that force the liquid into a radial expansion perpendicular to the plane formed by the jets, resulting in a consecutive chain of flat sheets bound by thick rims. In this context, LCs pose several challenges considering their viscosity, non-Newtonian behavior, and mesophase nature. Here, a precise control of temperature, thus mesophase, and pressure is demonstrated enabling the use of LCs in an impinging jet system. In particular, the system presented here delivers stable fluid chains of different sizes and thicknesses. The viscosity and non-Newtonian behavior of the LCs have a significant impact on the thickness of the chains as a function of the nozzle inner diameter, impinging angle, and radial distance from the impinging point. The flow rate, on the other hand, primarily affects the width and length of the liquid sheet.

Experimental Investigation of Chloride Ion Monitoring in Concrete Considering the Coupling Effect of Temperature and Humidity

Ag/AgCl electrodes have acquired significant research attention due to their crucial role in the electrochemical monitoring of chloride ion concentration. However, the electrode potential is susceptible to changes in temperature and humidity, and comprehensive investigations regarding the influence of moisture are lacking. Existing studies on Ag/AgCl electrodes have been qualitative, primarily focusing on analyzing the trend of electrode potential to detect variations in Cl- concentration. This study proposes an experimental method that enables precise control of temperature and humidity within concrete. The effects of temperature and humidity coupling on Ag/AgCl electrode potential in a concrete environment and a fundamental model were established correlating Ag/AgCl electrode potential with temperature, humidity, and chloride ion concentration, thereby enhancing the sensing accuracy. The developed model corrected errors from temperature and humidity coupling effects on the Ag/AgCl electrode potential. A quantitative investigation on using Ag/AgCl electrodes for monitoring Cl- concentration was conducted, facilitating their application in engineering and the development of non-destructive monitoring systems for chloride ions in concrete structures.

Synergistic effects of magnetic fields and Y-obstacles on a nanofluid-based split lid-driven thermal system

This study investigates the complex hydrothermal behavior in a novel split-driven square cavity filled with CuO-water nanofluid and featuring a Y-shaped obstacle. The research explores the interplay among mixed convection, magnetohydrodynamics (MHD), and geometric factors in a previously unexamined configuration. The upper wall is split into two isothermally heated, translating sections, while the bottom wall and Y-shaped obstacle provide cooling boundaries. Using finite element analysis, we examine the effects of Reynolds number (Re = 10-200), Rayleigh number (Ra = 103-106), Hartmann number (Ha = 0-70), and magnetic field inclination (λ = 0-150°) on flow patterns, heat transfer, and entropy generation. Energy flux vectors are utilized to analyze thermal energy transport dynamics. Key findings are as follows. (1) Increasing Re enhances fluid mixing, resulting in up to a 65% increase in the average Nusselt number (Nu). (2) Nu peaks at Ra ≈ 105, then slightly decreases due to complex force interactions. (3) Increasing Ha suppresses convection, reducing Nu by up to 30%. (4) Optimal heat transfer occurs at λ ≈ 75°. (5) The Y-shaped obstacle enhances heat transfer by up to 30%. These results provide insights for optimizing thermal management in applications requiring precise temperature control, potentially improving energy efficiency in advanced heat transfer systems.

Development of a Human Recombinant Collagen for Vat Polymerization-Based Bioprinting.

In light-based 3D-bioprinting, gelatin methacrylate (GelMA) is one of the most widely used materials, as it supports cell attachment, and shows good biocompatibility and degradability in vivo. However, as an animal-derived material, it also causes safety concerns when used in medical applications. Gelatin is a partial hydrolysate of collagen, containing high amounts of hydroxyproline. This causes the material to form a thermally induced gel at ambient temperatures, a behavior also observed in GelMA. This temperature-dependent gelation requires precise temperature control during the bioprinting process to prevent the gelation of the material. To avoid safety concerns associated with animal-derived materials and reduce potential issues caused by thermal gelation, a recombinant human alpha-1 collagen I fragment was expressed in Komagataella phaffii without hydroxylation. The resulting protein was successfully modified with methacryloyl groups and underwent rapid photopolymerization upon ultraviolet light exposure. The developed material exhibited slightly slower polymerization and lower storage modulus compared to GelMA, while it showed higher stretchability. However, unlike the latter, the material did not undergo physical gelation at ambient temperatures, but only when cooled down to below 10°C, a characteristic that has not been described for comparable materials so far. This gelation was not caused by the formation of triple-helical structures, as shown by the absence of the characteristic peak at 220nm in CD spectra. Moreover, the developed recombinant material facilitated cell adherence with high cell viability after crosslinking via light to a 3D structure. Furthermore, desired geometries could be easily printed on a stereolithographic bioprinter.

Oxidation-induced graded bandgap narrowing in Two-dimensional tin sulfide for high-sensitivity broadband photodetection

Two-dimensional (2D) layered group-IV monochalcogenides with large surface-to-volume ratio and high surface activity make that their structural and optoelectronic properties are sensitive to air oxidation. Here, we report the utilization of oxidation-induced gradient doping to modulate electronic structures and optoelectronic properties of 2D group-IV monochalcogenides by using SnS nanoplates grown by physical vapor deposition as a model system. By a precise control of oxidation time and temperature, the structural transition from SnS to SnSOx could be driven by the layer-by-layer oxygen doping and intercalation. The resulting SnSOx with a graded narrowing bandgap exhibits the enhanced optical absorption and photocurrent, leading to the fabricated SnSOx photodetector with remarkable photoresponsivity and fast response speed (<64 μs) at a broadband spectrum range of 520–1550 nm. The peak responsivity (7294 A/W) and detectivity (9.54 × 109 Jones) of SnSOx device are at least two orders of magnitude larger than those of SnS photodetector. Moreover, its photodetection performance can be competed with state-of-the-art of 2D materials-based photodetectors. This work suggests that the air oxidation could be utilized as an efficient strategy to engineer the electronic and optical properties of SnS and other 2D group-IV monochalcogenides for the development of high-performance broadband photodetectors.

A novel heat recovery VRF system: Principle and cooling performance analysis

Faced with an increasingly severe energy problem and increased demand for indoor comfort, heat recovery VRF systems have demonstrated remarkable potential for energy conservation. However, traditional heat recovery VRF systems need more suboptimal energy efficiency in terms of cooling and dehumidification and fail to guarantee precise temperature and humidity control in specific environments. In this study, a novel heat recovery VRF system that can achieve highly efficient cooling while ensuring precise humidity control is proposed. It can realize four primary operation modes by changing the function of indoor heat exchangers. The results showed that the optimal volume ratio of the two compressor cylinders was 1.4, which was used as the design parameter for the system. Compared to the single-evaporation temperature system, the proposed double-evaporation temperature system has better energy efficiency and dehumidification capacity in the cooling mode. The cooling coefficient of performance (COP) can be increased by 3.18 %–6.05 %, the compressor energy consumption can be reduced by 3.07 %–7.03 %, and the moisture extraction rate and latent heat ratio of the system can be increased by 5.6 %–33.3 %.

A Review of Viscosity Measurement Techniques for Semi-Solid Metal Fluids in Thixoforming Processes

This paper critically reviews two viscometry techniques: capillary viscometers and parallel plate compression (PPC) viscometers, which are used in the viscosity measurement of semi-solid metal (SSM) fluids for thixo routes. Capillary and PPC viscometers have emerged as valuable viscometers in the study of thixo routes of SSM, with insights into their unique flow behavior being explored. Thixoprocessing of SSM is particularly suitable for specific alloys, especially those with specific solidification properties such as eutectics. It is a method of thixoforming that uses a material's non-dendritic microstructure. The thixo method's viscosity measurement is challenging, requiring sample preparation, sophisticated equipment, precise temperature, and pressure control. Previous studies have lacked sufficient information on measurement methods, viscometers, and limitations to measuring viscosity for the thixo route of SSM. Hence, this study thoroughly examines the principles, advantages, limitations, and application areas of viscometry methods. Several factors influencing viscosity measurements, such as temperature, shear rate, and sample preparation, are discussed in detail. A comparative analysis is conducted to evaluate the performance and accuracy of capillary viscometers and parallel plate compression viscometers. This review will provide a comprehensive understanding of SSM's viscometry techniques and assist researchers and practitioners in selecting the most appropriate method for their specific applications in semi-solid metal processing and characterization.

Adaptability and growth of Hippocampus kuda and Oryzias melastigma under rapid temperature changes.

Temperature changes had a huge impact on the growth of aquaculture organisms, which mainly involved two parameters: the changing amplitude and the changing speed. Wide-adaptability and narrow-adaptability were divided by the amplitude, while fast-adaptability and slow-adaptability proposed in this article were divided based on the speed. Investigating the impact of the changing speed on artificial farming was vital. In this study, two fish species of wide-adaptability, Hippocampus kuda and Oryzias melatigma, were selected as research objects, explored the effects of temperature changing speeds on them under 2 changing amplitudes of 2°C and 4°C. The similarities and differences in their responses to temperature changes were analyzed and compared from the aspects of feeding, metabolism, physiology, immunity, and growth. The results showed that all 3 changing speeds (0.5°C/h, 1°C/h, and direct input) had no effect on the growth of O. melatigma under the 2°C amplitude, while there were significant differences in various aspects of H. kuda in the treatments with the speeds between 0.5°C/h and direct input, such as a significant difference in growth, in food intake, and in response speeds and response levels of several enzymes and related genes. Under 4°C amplitude, the impact of all 4 changing speeds (0.5°C/h, 1°C/h, 2°C/h and direct input) on both fish was more pronounced. H. kuda showed a significant difference of growth among 3 groups, and the critical safe speed was about 0.5°C/h in its heating treatments. And the growth decrease only occured the heating treatment of direct input in O. melatigma. Furthermore, some genes responded quickly and efficiently to the low-speed changes of temperature in H. kuda, but were inhibited in the treatments with high-speed changes. However, they can still express rapidly and efficiently in the high-speed treatments of O. melatigma, included several stress-related genes, lipid metabolic-related genes, and immune-related genes. Seen from these differences, the energy source used in H. kuda to resist stress was single and short-lived. So, under a long-term stress, H. kuda gradually transformed from normal physiological stress into pathological stress, leading to the outbreak of diseases. Therefore, for precise aquaculture of H. kuda, stricter and more precise control of environmental temperature is necessary to prevent rapid and big temperature changes from affecting the growth and survival of the seahorse.

PID-Based Temperature Stabilization for Silicon Photomultipliers Using Thermoelectric Cooling Devices

In this paper, we present a temperature stabilization system for Silicon Photomultipliers (SiPMs) using thermoelectric cooling devices controlled by a PID (Proportional-Integral-Derivative) controller. Maintaining a stable temperature for SiPMs and their associated front-end electronics is crucial for achieving consistent gain and noise minimization. Our system employs three CP1881-222 thermoelectric coolers per module and is managed by two ATMega1284p microcontrollers. One microcontroller handles the PID control routine, while the other functions as a TCP/IP client. The temperature is monitored using PT100 sensors connected via MAX31865 RTD converters, ensuring precise measurements. The PID algorithm efficiently corrects temperature deviations, maintaining an error margin of approximately ±0.2◦C. The system has been successfully deployed in the HASC subdetector of CERN’s NA62 experiment, where it maintains the SiPM temperature at 20.5◦C, enhancing the subdetector’s performance. The modular design of our PID controller system allows for adaptability to various experimental setups requiring precise temperature control.

Optimization of water supply parameters for enhanced thermal uniformity in aquaculture ponds: An experimental study based on orthogonal experimental design

The temperature distribution in aquaculture ponds plays a crucial role in the rearing of fish larvae. To achieve a more uniform temperature distribution in the pond and alleviate the problem of thermal stratification, precise control of pond temperature is essential. A recirculating aquaculture pond was taken as the test object. Single-factor experiments and orthogonal experiments were conducted to comprehensively test the aquaculture pond's water supply pipe layout, bend angle, perforation rate, and environmental conditions. Three evaluation indicators were used to analyze the temperature distribution of the aquaculture pond under various water supply pipe structures, leading to the identification of optimal structural configurations. The optimal structure I, obtained from single-factor experiments, was determined to be 2.5 m, 50 %, and 60°, while the optimal structure II, derived from orthogonal experiments, was 1.25 m, 75 %, and 30°. Both optimized structures exhibited significant temperature fluctuations in the pond during the summer season. However, Structure II demonstrated the lowest average temperature difference in the winter season, indicating its superior adaptability during winter. Moreover, Structure II could provide higher temperatures for shallow areas with depths greater than 600 mm, making it more suitable for fish larvae cultivation. Additionally, local devices effectively decreased temperature variations by 17.5 % within the pond. Furthermore, energy consumption output was evaluated for different operational conditions. The results showed that Structure II had the lowest energy consumption output during the summer season. In contrast, during the winter season, the energy consumption output increased by approximately 12 %, indicating significant energy-saving potential in aquaculture ponds during winter.