1445 results about "Relative humidity" patented technology

The invention belongs to the technical field of intelligent agriculture, and discloses a canopy-atmospheric environment information-based soil water content prediction method and system, and the method comprises the steps: setting a canopy and atmospheric environment monitoring unit in a field, and synchronously collecting the canopy temperature, wind speed, relative humidity, and six-dimensional environment parameters of atmospheric temperature, wind speed and relative humidity; the crown temperature difference is calculated after preprocessing; the method comprises the following steps: constructing a training set by utilizing measured data of soil relative water content, constructing a soil water content prediction model by adopting a random forest algorithm, screening and confirming an optimal prediction model through grid search and cross validation, and screening key features by combining an SHAP value; the water demand is automatically calculated according to a pre-established crop whole-growth-period drought stress threshold table and a dynamic irrigation decision formula, and meanwhile, the adaptation of a general model to a regional specific model is realized by constructing an environmental parameter-actually measured water content database and transfer learning, so that the soil water content state is accurately predicted, and the soil quality is improved. And a scientific basis is provided for precise irrigation.

The invention discloses a mass concrete temperature evolution analysis model based on a multi-field coupling model. The mass concrete temperature evolution analysis model comprises the following steps: S1, establishing a concrete hydration field model containing temperature and relative humidity correction; s2, establishing a temperature field model containing common characterization of concrete matching, hydration degree and relative humidity; s3, establishing a humidity field model for correcting an early concrete water storage function and a humidity transmission coefficient based on the hydration degree; s4, establishing a water cooling model coupled with the concrete temperature field based on the non-isothermal pipeline flow; and S5, establishing an early concrete temperature rise analysis model based on hydration-heat-wet-water cooling coupling based on a finite element method. According to the method, environmental factors, material factors, construction factors and maintenance factors in the concrete hydration process are fully combined, the application scene is more comprehensive, and the accuracy is higher.

The present invention discloses a floor radiation cooling system and an anti-condensation control method, which relate to the technical field of radiation air conditioning. The method comprises: real-time collection of indoor temperature and humidity, electric three-way valve opening, water pump flow and fresh air unit parameters; using particle swarm algorithm (PSO) to optimize radial basis function neural network (RBF) weights and construct a PSO-RBF prediction model; inputting indoor air temperature, relative humidity, fresh air speed, fresh air humidity, valve opening and water pump flow into the model, outputting surface temperature and calculating condensation risk value with current dew point temperature, dynamically regulating fresh air speed and humidity to achieve anti-condensation; and adjusting the radiation surface temperature based on the PMV thermal comfort model to maintain thermal comfort. The method uses a dual control mechanism to ensure that the radiation surface is prevented from condensation while using the radiation surface to independently bear the sensible heat load, effectively avoiding mold growth and maintaining a stable indoor thermal environment.

Systems and methods for providing dehumidification to an enclosed space can include a dehumidification unit in a supply air plenum that receives return air and a regeneration unit in a scavenger air plenum that receives outdoor air. The system can operate in a wet mode and a dry mode, depending on outdoor air conditions and a relative humidity setpoint for the enclosed space. The dehumidification unit and regeneration unit are both operational in the wet mode to dehumidify the return air and regenerate dilute desiccant. In the dry mode, the dehumidification unit and regeneration unit are not needed, and dry outdoor air can be supplied to the enclosed space. A heat recovery system utilizes waste heat from either return air or scavenger air, depending on the operating mode, to heat the outdoor air before it is supplied to the enclosed space or before it is used for regenerating desiccant.

An atmospheric water generation system comprises water vapor consolidation systems configured to increase the relative humidity of a controlled air stream prior to condensing water from the controlled air stream. The water vapor consolidation system comprises a fluid-desiccant flow system configured to decrease the temperature of the desiccant to encourage water vapor to be absorbed by the desiccant from an atmospheric air flow. The desiccant flow is then heated to encourage water vapor evaporation from the desiccant flow into a controlled air stream that circulates within the system. The humidity of the controlled air stream is thereby increased above the relative humidity of the atmospheric air to facilitate condensation of the water vapor into usable liquid water.

The invention belongs to the technical field of simulation analysis, and particularly relates to a medium-high voltage switch cabinet internal humidity inversion calculation method based on simulation analysis, which comprises the following steps: establishing a geometric model of a switch cabinet, importing the geometric model into finite element simulation software to obtain a simulation analysis model, adding each physical field and computational domain and boundary conditions thereof, and calculating the internal humidity of a medium-high voltage switch cabinet. All the physical fields are coupled, and mesh generation is carried out; performing numerical solution on the simulation analysis model by using a transient solver to obtain a temperature and humidity distribution condition in the switch cabinet; the simulation analysis model is optimized, a simulation data set is constructed, and a PINN is trained; based on the environment temperature and humidity and the operation current collected in the actual operation of the switch cabinet, the trained PINN is used for prediction, and the steady-state relative humidity of the current transformer is obtained. According to the invention, based on the limited boundary monitoring data, efficient and accurate reconstruction of the humidity field of the key area in the switch cabinet is realized, and a feasible path is provided for equipment state sensing and condensation risk early warning.

The present application relates to hydrogen production technology field, especially to a kind of methanol hydrogen production method, comprising the following steps: S10: methanol water is heated and vaporized to obtain methanol water vapor;S20: methanol reforming reaction obtains hydrogen mixture gas;S30: after cooling treatment to hydrogen mixture gas, through water washing tower absorption unreacted methanol water, then, adjust the relative humidity and temperature of hydrogen mixture gas;S40: hydrogen mixture gas is input into carbon dioxide absorption tower to remove carbon dioxide;S50: after removing carbon dioxide, product hydrogen is obtained and input hydrogen tank storage to supply user end.The above-mentioned methanol hydrogen production method, by methanol water vapor reforming hydrogen treatment, obtains hydrogen mixture gas.Again, hydrogen mixture gas is purified to obtain product hydrogen with very low carbon monoxide content, with raw material easy to transport, the hydrogen purity of output is high, equipment construction cost is low, and energy consumption is low and the like advantages, reach the purpose of expanding hydrogen application range.

As the withering process of tea leaves takes a long time to reach a desired moisture level, estimating when it is time to move to the next step to reach the target tea leaf moisture is difficult and inefficient. Method and system disclosed herein provide an approach for withering schedule prediction of tea leaves. The system, by performing a spectral data analysis on an image of a plurality of tea leaves, estimates the moisture percentage in the plurality of tea leaves, for a selected time stamp. Based on the predicted moisture level, a current temperature value, a current relative humidity value, and a current time stamp, the system generates a withering schedule for the plurality of tea leaves. The generated withering schedule is fine-tuned based on a course correction of an impact of deviation in one or more ambient parameters on the prediction of the withering schedule.

The invention discloses an existing wind power blade electrothermal film deicing control method based on big data, and relates to the technical field of wind turbine generator operation control and ice prevention and removal. Frost ice / glaze ice probability output by an ice type discrimination model does not only give an alarm any more, but is directly converted into an increase / decrease coefficient constrained by boundary and monotonicity; energy can be fully put in a glaze ice scene, and overheating and over-consumption can be avoided in a frost ice scene; according to the method, the change trend of wind speed, temperature and relative humidity is introduced as modulation factors, the working condition of forming / turning glaze ice is responded in advance, and insufficient deicing caused by static threshold hysteresis is reduced; according to power deviation correction, a unit wind speed-power curve serves as a reference, a dead zone, segmented gain and accumulative saturation structure is adopted, on the premise of not depending on an external icing sensor, extrinsic performance of pneumatic degradation is closed into controlled quantity, sensitivity and stability are considered, and start-stop oscillation and duration drift are reduced.

β-Ketoenamine covalent organic frameworks (COFs) provide remarkable water sorption capabilities and stable adsorption–desorption cycling, particularly under low relative humidity (RH) conditions.

The invention discloses an automatic demisting control system for a demisting mirror, belongs to the technical field of smart home and automatic control, and aims to solve the problems that an existing demisting mirror is inconvenient to use and wastes energy due to the fact that the existing demisting mirror depends on manual operation. According to the system, the mirror surface temperature is detected in real time through the mirror surface temperature sensor, environment data are collected in combination with the environment temperature and humidity sensor, a dew point temperature calculation module and a dynamic threshold module are arranged in the control unit, and the current dew point temperature is calculated based on the environment temperature and the relative humidity; and dynamically adjusting a demisting trigger threshold value according to a difference value delta T between the mirror surface temperature and the dew point temperature. The heating wires are distributed on the back face of the mirror body at intervals, heating gears are selected according to the temperature difference change rate and the humidity change rate, and accurate temperature control is achieved. According to the system, through a dynamic threshold value and graded power adjusting technology, the rapid demisting and energy-saving requirements are considered, the system is suitable for automatic mirror surface demisting in humid environments such as bathrooms and swimming pools, the user experience is improved, and the energy consumption is reduced.

An atmospheric water generation system comprises water vapor consolidation systems configured to increase the relative humidity of a controlled air stream prior to condensing water from the controlled air stream. The water vapor consolidation system comprises a fluid-desiccant flow system configured to decrease the temperature of the desiccant to encourage water vapor to be absorbed by the desiccant from an atmospheric air flow. The desiccant flow is then heated to encourage water vapor evaporation from the desiccant flow into a controlled air stream that circulates within the system. The humidity of the controlled air stream is thereby increased above the relative humidity of the atmospheric air to facilitate condensation of the water vapor into usable liquid water.

A method for managing environmental conditions of an information handling system includes obtaining an ambient temperature and an ambient humidity of an environment proximate to the information handling system. The method also includes determining a target relative humidity for the information handling system and determining a target temperature for the information handling system based on the target relative humidity, the ambient temperature, and the ambient humidity. Further, the method includes determining that the target temperature is within an acceptable range of temperatures. In addition, the method includes adjusting an amount of air recirculated through the information handling system, and adjusting the amount of air recirculated is based on the determination that the target temperature is within an acceptable range of temperatures.

The invention discloses an airplane ice accretion monitoring method fusing millimeter wave cloud radar and ground-based microwave radiometer data, which comprises the following steps: step 1, taking temperature profile and relative humidity profile data monitored by a ground-based microwave radiometer in a test area in real time as input quantities to obtain airplane ice accretion index values corresponding to all profile data; step 2, obtaining a reflectivity Z profile of liquid water particles in a test area and a total liquid water value LWP on an observation path; step 3, carrying out inversion to obtain a liquid water content LWC profile in the cloud on the observation path; step 4, taking an overlapped area of an area of which the temperature profile data of the foundation microwave radiometer is less than 0 DEG C and an area of which the inverted liquid water content data of the cloud is greater than 0, a supercooled water area in the cloud is formed; and step 5, analyzing whether the ice accumulation area in the step 1 and the supercooled water area in the step 4 are overlapped or not, if yes, representing that ice accumulation occurs in the air, and if not, representing that no ice accumulation occurs in the air. According to the method disclosed by the invention, a millimeter wave cloud radar and ground-based microwave radiometer active and passive combined detection technology is adopted, the total amount of liquid water and a water vapor profile in the airport airspace are detected, the distribution of supercooled liquid water in cloud in the airport airspace is inverted, and the distribution of a potential icing area of an aircraft is monitored in real time.

The invention relates to the technical field of ice and snow environment simulation, and discloses an ice and snow environment simulation test method based on multi-field coupling. The method comprises the following steps: collecting a dynamic multi-field data set in a target ice and snow environment, wherein the dynamic multi-field data set covers a periodic temperature change sequence, a relative humidity fluctuation sequence and surface ice layer thickness real-time monitoring data; carrying out multi-physics field coupling numerical simulation processing to generate coupling field distribution characteristics including an axial heat conduction coefficient gradient, a radial fluid velocity cumulant and a tangential ice layer stress fluctuation coefficient; calling a pre-configured ice and snow growth simulation model to execute ice layer evolution analysis to obtain an ice layer growth rate prediction value and a high-risk icing area position identifier; performing environment dynamic compensation correction on the ice layer growth rate prediction value by using the correlation characteristic of the relative humidity fluctuation sequence and the material heat capacity attribute; based on the high-risk icing area position identification, scientific guidance is provided for related protection in the ice and snow environment.

The invention relates to the technical field of grain depot ventilation prediction, and discloses a grain storage ventilation decision-making method based on GNN and Cross-Attention, and the method comprises the steps: collecting internal temperature and humidity data of a grain depot, external temperature and humidity data of the grain depot, weather data and grain pile temperature data in real time; and the collected grain pile temperature data and weather data are preprocessed respectively, the grain balance relative humidity, the atmosphere dew point temperature and the grain dew point temperature are calculated and serve as input of a pre-trained ventilation decision model, and a classification result of ventilation decisions is obtained. Based on the temperature and humidity information of the air in the grain depot, the ventilation of the grain depot is comprehensively decided by combining the external temperature and humidity of the grain depot, the dew point data, the weather data and other information, the temperature characteristics of the grain depot are more accurately extracted, and the ventilation decision of the grain depot is more reliable.

The invention relates to the technical field of welding, in particular to a hot riveting welding head synchronous temperature control method and system based on the temperature change rate, and the method comprises the steps: executing full-power heating pulse triggering operation on a welding head, calculating the pulse duration according to a start timestamp and an end timestamp, calculating the temperature rise, and eliminating peak noise through a digital filtering algorithm; environment temperature and relative humidity are collected in real time, and equivalent heat capacity is calculated; the initial temperature difference between any welding heads is calculated, and a dynamic target temperature curve is constructed; and calculating an actual temperature change rate, synchronously extracting a target change rate of the dynamic target curve at a corresponding moment, calculating a change rate deviation between the two change rates, judging whether intervention adjustment is needed or not, calculating an output signal by using an incremental PID algorithm if intervention adjustment is needed, and adjusting the heating power according to the output signal. According to the scheme, the stability of the hot riveting welding quality is effectively improved by accurately quantifying the thermal characteristics of the heterogeneous welding head, dynamically planning a personalized temperature rising track and performing high-frequency closed-loop regulation and control.

The invention discloses a preparation method of a photo-thermal super-hydrophobic coating with excellent anti-icing / deicing performance in a low-temperature and high-relative-humidity environment, which comprises the following steps of: firstly, growing photo-thermal Cu-MOF (Metal Organic Framework) nano particles on the surfaces of fibrous clay mineral nano particles with low heat conductivity coefficient in situ to construct composite photo-thermal particles with a two-stage nano / nano structure; the preparation method comprises the following steps: preparing nano-particles, then carrying out low surface energy modification on the nano-particles, introducing a low-heat-conductivity-coefficient binder, inducing the binder to generate phase separation through a non-solvent to form a micron-scale binder / low-surface-energy nano-particle aggregate, and finally, spraying to construct the photo-thermal super-hydrophobic coating with a three-level micro / nano / nano structure. The three-level micro / nano / nano structure of the coating simultaneously endows the coating with excellent photo-thermal performance in a low-temperature and high-relative-humidity environment and Cassie-Baxter state stability of liquid drops on the surface of the coating, so that the coating has excellent passive anti-icing / frosting and active deicing / defrosting performance in the environment. The low heat conduction characteristic of the coating further inhibits heat exchange between the base material and water drops, so that the passive anti-icing / frosting performance of the coating is further improved. In addition, the invention also has the advantages of simple preparation method, large-area preparation and the like, and lays a solid foundation for the practical application of the photo-thermal super-hydrophobic anti-icing coating.

The invention discloses an insulation state evaluation method for a voltage transformer online monitoring device, and the method comprises the following steps: obtaining an original dielectric loss angle tangent value through a dielectric loss tester, and collecting the temperature and relative humidity through an environment sensor; performing temperature and humidity compensation on the collected dielectric loss angle tangent value to obtain a compensated dielectric loss angle tangent value; performing trend prediction on the compensated dielectric loss angle tangent value based on an autoregressive integral moving average model to obtain a predicted value; judging an abnormal state by comparing a predicted value with a dynamic threshold value; performing risk assessment by integrating the equipment state parameters, and outputting a corresponding maintenance decision according to an assessment result; according to the invention, the interference of environmental factors on the measurement of the dielectric loss angle tangent value is eliminated, and the measurement accuracy is improved; the abnormal change trend of the dielectric loss value is found in advance through trend prediction, and early warning is realized.

The invention discloses an air conditioner automatic control method and system based on a cold and heat source machine room, and relates to the technical field of air conditioner automatic control. Calculating a cold and heat source switching index K1 according to the deviation between the outdoor temperature T1 and the target temperature T0 in combination with the change trend of the relative humidity H1; when the cold and heat source switching index K1 exceeds a preset threshold value, a load prediction module is started, and a load prediction value P1 is generated; and according to the load predicted value P1, the rotating speed of the water pump is controlled in a gradient adjustment mode, and the valve opening V1 is dynamically adjusted through the temperature difference between the water supply temperature T2 and the water return temperature T3. The system operation accuracy, the energy utilization efficiency and the adjustment flexibility are remarkably improved, the rotating speed of the water pump and the opening degree of the valve can be accurately adjusted dynamically in real time according to outdoor temperature and humidity changes and equipment operation characteristics, and the technical problems that an air conditioning system is inaccurate in control and large in energy consumption fluctuation are effectively solved.

The invention discloses a method for performing quality control on hydrometeorological data by using relevance, and relates to the field of marine meteorology. According to the rule of hydro meteorological element data, data quality control is carried out by using the relevance between elements, namely the relevance quality control method. The method comprises the following steps: firstly, sorting data to enable the data to contain time, place, instrument state and other information, performing conventional quality control inspection and identifying abnormal values; the element relevance is analyzed and divided into natural relevance and algorithm relevance. According to natural association, data exception is judged by checking reasonability and contradiction of element values; according to algorithm association, after abnormity is detected in conventional quality control, it is judged that the associated derivative elements are abnormal. The correlation quality control covers a plurality of elements such as time, place, salinity, vector, relative humidity, wind-wave-flow and the like, and emphasizes that correlation is judged according to element observation sources and modes, so that excessive quality control is prevented. The method is clear in process and high in expansibility, suspicious or abnormal data can be effectively detected, and a reliable quality control method is provided for quality control of hydro meteorological observation data.

The invention discloses a vegetation index time sequence prediction method and device based on deep learning, and the method comprises the following steps: obtaining and processing historical period vegetation indexes and environmental factor data of a preset time period, and obtaining NDVI, EVI and kNDVI data as vegetation indexes, environment factor data including temperature, rainfall, evapotranspiration, wind speed, relative humidity and soil humidity; by determining the intensity and direction of the linear relation between the environmental factors and the vegetation indexes, the environmental factors with high correlation with the vegetation indexes are selected; a CNN-BiLSTM-AM model comprising an input layer, a CNN layer, a BiLSTM layer, an AM layer and an output layer is constructed to predict a vegetation index time sequence, environmental factors with high correlation serve as input data, and NDVI, EVI and kNDVI vegetation indexes serve as output prediction targets. The technical process is simple and clear, and the accuracy of vegetation index time sequence prediction is greatly improved.

The invention relates to the technical field of pipeline safety monitoring and water seepage prevention early warning, in particular to a water seepage prevention early warning system driven by complex temperature and humidity environment edge calculation, which comprises the following modules: an environment and water immersion data acquisition module used for acquiring temperature, relative humidity, water immersion signals and auxiliary evidence in real time at edge nodes and performing preprocessing; and the temperature and humidity coupling dew point judgment module is used for calculating a dew point at the edge node based on the temperature and humidity data and generating condensation negative evidence. According to the method, temperature and humidity and water immersion data are collected at edge nodes and preprocessed, condensation negative evidence is generated based on the temperature and humidity data and fused with water immersion positive evidence to form a Markov chain, meanwhile, an environment base line is established, and a threshold value is adjusted in a self-adaptive mode, so that continuous monitoring and closed-loop judgment of the water seepage state are achieved; therefore, the problems that most traditional pipeline water seepage monitoring systems depend on a remote server, and judgment lags and misinformation is caused by the complex environment and the static threshold value are solved.

The invention provides an air conditioner and a control method and device thereof, a storage medium and a computer program product, and the method comprises the following steps: after the air conditioner is started for refrigeration and operation, determining to enter an air supply mode or a temperature and humidity control mode according to indoor temperature and indoor relative humidity; if it is determined that the air conditioner enters the temperature and humidity control mode, the current building load and the corresponding sensible heat ratio of the air conditioner are obtained according to indoor and outdoor environment parameters and set parameters of the air conditioner; according to the obtained current building load of the air conditioner and the corresponding sensible heat ratio, the compressor frequency, the inner fan rotating speed and the outer fan rotating speed of the air conditioner are calculated; according to the calculated compressor frequency of the air conditioner and the operation state parameters of the air conditioner, the opening degree of a throttling device of the air conditioner is calculated; and controlling the air conditioner to operate according to the compressor frequency, the rotating speed of the inner fan, the rotating speed of the outer fan and the opening degree of the throttling device which are obtained through calculation. According to the scheme, the humidity can be accurately controlled in the cooling process of the air conditioner, and the indoor comfort is improved.

The invention relates to a phase perception residual learning-based rice drying moisture content fusion prediction method, which comprises the following steps of: acquiring multi-dimensional data in a rice drying process, preprocessing, dividing three drying phases based on a change rate of relative humidity of waste gas, and continuously optimizing; an improved Page model is constructed, drying coefficients k and n are fitted in stages, k is associated with the hot air temperature through an Arrhenius formula, n is associated with the hot air temperature through a quadratic equation, and a physical baseline predicted value is generated after parameters are optimized through a deep bed test; calculating a residual error between the actual moisture content and the physical baseline, and training the LSTM network by taking the residual error as a target to enable the LSTM network to learn nonlinear features which cannot be described by a physical model; and fusing the physical baseline of the improved Page model and the residual error predicted by the LSTM to obtain a final fusion prediction result. The method not only ensures the physical rationality of the prediction result, but also improves the precision and generalization ability, and is suitable for intelligent regulation and control of the rice drying process.

The invention is suitable for the technical field of rainfall forecast correction, and provides a regional short-term rainfall quantitative forecast machine learning correction method integrated with weather system information, and the method comprises the steps: determining an initial forecast factor based on meteorological elements in an ECMWF mode, the meteorological elements comprise a precipitation field, ground transformation, convection effective potential energy, UV wind fields of 500hPa, 850hPa and 925hPa, relative humidity, temperature and vertical speed; taking the dichotomy labels corresponding to the 500hPa slot line and the tangent line between 850hPa and 925hPa as newly added forecast factors, and constructing a four-dimensional training set according to the initial forecast factors and the newly added forecast factors; converting the four-dimensional training set into a three-dimensional training set; training a random forest regression model through the three-dimensional training set, and outputting a rainfall forecast field within a preset time; according to the CMASH3 mode rainfall forecast data and a preset judgment logic, dynamically correcting the rainfall forecast field within a preset time, and generating a target rainfall forecast product; and the accuracy of heavy rainfall forecasting is effectively improved.

A lyophilization method for lyophilizing products inside one or more vials within a lyophilization chamber is disclosed which includes humidifying a charge gas to a predetermined relative humidity, cooling shelves in the lyophilization chamber to a predetermined temperature, pressurizing the chamber with the humidified charge gas to a pressurization threshold to thereby achieving a target relative humidity level within the lyophilization chamber, and suddenly releasing pressure within the lyophilization chamber until a depressurization threshold is reached in a short time interval up to about 4 seconds, during the depressurization, product inside one or more vials nucleate.

The invention discloses an assimilation method based on a GNSS multi-dimensional water vapor cooperation WRF meteorological mode. The assimilation method comprises the steps of 1, GNSS water vapor inversion; 2, assimilating the precipitable water quantity inversed by the GNSS for the first time; 3, carrying out GNSS three-dimensional chromatography inversion; 4, interpolating the water vapor density value of the three-dimensional chromatography grid into the forecast three-dimensional grid to obtain a water vapor density value of a three-dimensional interpolation grid which is the same as the forecast three-dimensional grid; 5, carrying out inversion on the water vapor density value of the three-dimensional interpolation grid and the temperature data of the forecast three-dimensional grid to obtain a relative humidity profile; and 6, assimilating the relative humidity profile again. The method is reasonable in design, first assimilation is carried out by using the precipitable water volume inverted by the GNSS, the relative humidity profile is obtained by using the three-dimensional water vapor density and the temperature data of the first assimilation, the relative humidity profile is assimilated again based on the WRF meteorological mode, assimilation is effectively carried out by using the three-dimensional water vapor density data, and the meteorological parameter forecasting precision is improved.

The invention relates to a method for improving the diapause egg rate of silkworm germplasm resources, which comprises the following steps: during the period from pupation completion to silkworm moth eclosion, illumination period regulation of 8-hour illumination and 16-hour darkness is adopted, a light source does not contain an ultraviolet wave band, the illumination intensity is 350lx-600lx, and the light source is uniformly distributed; the temperature in the illumination period is maintained at 26-28 DEG C, the temperature in the dark period is reduced to 23-25 DEG C to form a day-night temperature difference, and the temperature change and the illumination period are switched synchronously or adjusted gradually in stages; the relative humidity in the illumination period is controlled to be 70-75%, the relative humidity in the dark period is improved to be 75-85%, and the humidity change is synchronous with illumination period switching. The method is mainly used for silkworm germplasm production by regulating and controlling the photoperiod to cooperate with temperature and humidity changes and simulating a natural autumn cooling signal to induce diapause, the storable and planned production of silkworm eggs is guaranteed, and resource waste is reduced.

This invention addresses the challenge of thermal comfort in hot-humid tropical climates, where factors like solar radiation, humidity, and air temperature significantly affect indoor conditions. The patented hybrid attic ventilation technique operates continuously over 24 hours to improve ventilation in attics, which are crucial for maintaining overall building thermal performance. Field studies comparing a traditional attic setup with one utilizing the hybrid ventilation system were conducted in two typical one-storey terrace houses. Using Building Information Modeling (BIM) for energy consumption analysis, the results indicated that the hybrid system reduced indoor temperature by 1°C and relative humidity by 7%, leading to a notable 10% reduction in overall energy consumption. This innovative hybrid technique demonstrates enhanced thermal comfort and energy efficiency by leveraging both nighttime and daytime ventilation, making it a sustainable solution for residential buildings in tropical regions.