Thermal Response Model Research Articles

Synthesis and Analgesic Properties of Prodrug Bipharmacophore Compounds Based on Pyridoxine and Ketorolac

Prodrug bipharmacophore anti-inflammatory compounds based on pyridoxine and ketorolac were synthesized. A new laboratory method was developed to achieve > 98 % purity of these compounds, without the use of column chromatography. Compared to ketorolac tromethamine, which is the most potent non-opioid analgesic, both compounds exhibited lower toxicity (LD50 > 2000 mg/kg), while maintaining comparable analgesic efficacy in a model of acute thermal pain response.

Active phase and amplitude temperature control method for cryostat: A case in the thermodynamic temperature international comparison system

Achieving highly stable temperature control is essential for cryostats. However, the cryocooler used in cryostats, such as the pulse tube cryocooler, produces regular sinusoidal temperature fluctuations due to its inherent working principles. To establish a highly stable temperature environment, an active phase and amplitude control method for suppressing temperature fluctuation is proposed in this paper, by which the optimal phase and amplitude can be predicted in theory. To validate this approach, a thermal response model was developed based on experiments conducted in the thermodynamic temperature international comparison cryostat at approximately 3.7 K. Based on this model, we conducted both single-stage and multi-stage active temperature control experiments. The results demonstrate that the temperature control effect is the best when the active temperature control current is added at the second cold head, the fluctuation of the comparison copper block from 3.3mK to 0.166mK with 94.9 % suppression rate. The multi-stage joint temperature control reduced the temperature fluctuation with an attenuation rate of 95.4 %. These findings offer significant potential for improving temperature stability in future thermodynamic temperature comparison experiments.

A GIS-coupled thermal response model for predicting the population growth potential of the red cotton bug, Dysdercus koenigii (Fabricius) (Hemiptera: Pyrrhocoridae) in India under climate change conditions

Recently, the red cotton bug has become a significant menace to cotton in India. With the potential for increased habitat suitability due to predicted temperature rise of 2.5 °C under future climate change in India, this pest could become even more severe in certain regions. Addressing the knowledge gap on the temperature-driven population growth of this pest is crucial for developing a climate-resilient pest management strategy. In this study, life history data gathered at various constant temperatures (15 °C–35 °C) were used to estimate temperature thresholds and thermal requirements for the red cotton bug development. Stochastic estimation of life table parameters and validation with real-time weather data were performed. The phenology model, integrated into a geographic information system, projected the future pest status based on SSP126 temperature change scenarios for the year 2050. The temperatures between 8.35 and 10.83 °C were estimated as lower developmental thresholds for various immature life stages. The optimum and upper threshold temperatures estimated for different life stages ranged between 22.14 – 28.32 °C and 35.80–39.08 °C, respectively. Thermal requirements of 447.97° days for life cycle completion were estimated. The optimum immature survival rates (>70%) were observed at temperatures between 25 and 30 °C. The temperature-dependent decrease in generation times from 90.45 days (15 °C) to 25.44 days (35 °C) was observed, whereas maximum fecundity was recorded at 32 °C. Simulation at fluctuating temperatures across different cotton growing locations provided reasonably similar results on potential population increase (finite rate of increase: 0.99–1.04 females/female/day and a generation time of 44.25–83.97 days). Risk mapping highlighted moderate to high suitability (ERI >0.4, GI > 6, and AI >4) of various cotton growing areas under current climate, and projected shifts in suitability under future climate change. The study has generated information valuable for implementing effective and timely pest management strategies for red cotton bug. Integrating the field observations with model outputs can enhance a practical understanding of red cotton bug dynamics.

Ablation simulation of integral woven gradient three‐dimensional thermal protection structures for planetary exploration

AbstractFor the harsh entry environment and higher thermal protection requirements, two structures of three‐dimensional woven gradient thermal protection materials were designed and prepared with the deep space exploration thermal protection system as the object. They are 3D orthogonal woven, 2.5D layer‐to‐layer angle interlock woven, 2.5D layer‐layer angle interlock woven structure(OLL) composite and 3D orthogonal woven, angle 2.5D layer‐to‐layer angle interlock woven, honeycomb structure(OLH) composite. Two materials were prepared and examined by ablation in an oxygen‐acetylene flame. A three‐dimensional macroscopic ablation model was established on the basis of the experiment, and the model was verified to be accurate and effective, which can well respond to the pyrolytic ablation process of the materials. The two designed materials are applied to the outsole of MSL by simulation, and the three‐dimensional response during the entry into Mars is simulated and analyzed in comparison with the thermal protection performance of PICA material. Both materials show better thermal protection than PICA and can be used as a reference in the selection of thermal protection materials.Highlights Two kinds of 3D gradient woven thermal protection materials are designed. A 3D thermal protection system response model is established. The three‐dimensional response during entry was analyzed. Thermal protection of the material is superior to that of PICA.

Accurate modeling of thermal-optical performance for a lightweight SiC mirror

The SiC mirror has excellent structural rigidity and thermal stability, making it widely applicable in high-power optical systems. This manuscript aims to establish a coupled analysis model of thermal-optical performance for a lightweight SiC reflector under high-power laser irradiation. First, based on the Fourier principle, the transient temperature rise of the mirror is analyzed using the finite element method, considering boundary conditions such as heat source and convective radiation. A transient thermal response model for the mirror is established. Then, the reflective surface deformation is solved based on the mirror temperature field. By processing the data of node deformation, the decrease in the mirror surface shape accuracy (RMS) value is obtained. Finally, the experimental platform is built to measure the transient temperature rise and wavefront aberration change of the mirror after high-power laser excitation. Based on the deviation between the calculated data of the analysis model and the measured data, thermodynamic parameters in the analysis model are adjusted according to the principle of minimum residual. The research findings of this manuscript can be utilized for accurately predicting the temperature rise and optical degradation of SiC mirrors under high-power laser irradiation and provide a theoretical basis for the subsequent design of actively compensating methods for thermal-induced distortions.

Re-assessing thermal response of schistosomiasis transmission risk: Evidence for a higher thermal optimum than previously predicted.

The geographical range of schistosomiasis is affected by the ecology of schistosome parasites and their obligate host snails, including their response to temperature. Previous models predicted schistosomiasis' thermal optimum at 21.7°C, which is not compatible with the temperature in sub-Saharan Africa (SSA) regions where schistosomiasis is hyperendemic. We performed an extensive literature search for empirical data on the effect of temperature on physiological and epidemiological parameters regulating the free-living stages of S. mansoni and S. haematobium and their obligate host snails, i.e., Biomphalaria spp. and Bulinus spp., respectively. We derived nonlinear thermal responses fitted on these data to parameterize a mechanistic, process-based model of schistosomiasis. We then re-cast the basic reproduction number and the prevalence of schistosome infection as functions of temperature. We found that the thermal optima for transmission of S. mansoni and S. haematobium range between 23.1-27.3°C and 23.6-27.9°C (95% CI) respectively. We also found that the thermal optimum shifts toward higher temperatures as the human water contact rate increases with temperature. Our findings align with an extensive dataset of schistosomiasis prevalence in SSA. The refined nonlinear thermal-response model developed here suggests a more suitable current climate and a greater risk of increased transmission with future warming for more than half of the schistosomiasis suitable regions with mean annual temperature below the thermal optimum.

Optimal Scheduling of Micro-Energy Grid Based on Pareto Frontier Under Uncertainty and Pollutant Emissions

With the continuous improvement of micro-energy grid, in order to reduce carbon emissions and environmental pollution, a multi-objective optimization operation strategy considering the distributed energy generation uncertainty, environmental factors, and self-supply rate is proposed in this paper. First, to simulate the uncertainty of distributed energy, we used the three-parameter Weibull distribution to simulate the wind power. Then, for the load side, an innovative electric and thermal comprehensive demand response model is proposed. Different from the traditional micro energy network that only considers the heat energy balance, this paper also considers the thermal inertia of buildings to more accurately describe the characteristic of the heat load. Meanwhile, on the basis of economic factors, the abandon rate of distributed energy, environmental coefficient and self-sufficiency rate are also regarded as three objective functions. Finally, in order to obtaining a set of solutions at the Pareto front, the entropy-weighted TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method is introduced to obtain the global optimal solution. Simulation study of multiple scenarios shows the effectiveness of the proposed method. Compared with the method that considers only economic costs, the pollutant emissions are reduced by 50kg and self-power supply rate is increased by 20%.

A handy model for the dynamic thermal response of the building-plant system

This paper presents a novel approach for predicting the unsteady indoor room temperature as resulting from the interrelation among the characteristics of the thermal plant, the temperature regulation system, and the envelope, allowing an easy-to-handle but meaningful description. A finite element model is built by dividing the analysis domain into two separate sub-systems suitably coupled. The former represents the 1D unsteady composite wall, the latter describes the inner ambient regarded as a lumped thermal system. The development of optimal thermal regulation strategies in terms of comfort and energy savings is made easier. Simulation results revealed that a good level of comfort can be ensured by adopting different thermal regulation strategies for ‘light’ and ‘massive’ envelopes.

Numerical modeling of non-uniform indoor temperature distribution for coordinated air flow control

The indoor thermal environment is usually non-uniformly distributed in parameters such as temperature and velocity. For precise control of indoor environment, it is necessary to figure out the indoor non-uniform temperature distribution (INUTD) that empowers independently zone control according to the different requirements of occupants. Computational Fluid Dynamics (CFD) tool is usually used to obtain the INUTD, but it consumes huge computational resources and time, which may not be suitable for coupling with control system. To address this research question, this study proposes a numerical modeling method for predicting the INUTD and air flowrate response of multiple diffusers for coordinated air flow control. Firstly, we establish a dataset with 5000 cases, along with the results of INUTD for each case. Then two models, namely room thermal response model (RTRModel) and air flowrate prediction model (AFPModel), are developed by machine learning algorithms to predict indoor temperature and supply air flowrate, respectively. The results show that proposed models are both fast in prediction, less than 1 s for each case. The standard deviation of error in RTRModel developed with support vector machine algorithm is 0.0041 while that in AFPModel developed with Convolutional Neural Network algorithm is 0.0198. Further, a comparative analysis has been conducted between the AFPModel with and without optimization algorithm. The results reveal that using optimization algorithm is more accurate, but it takes more time. While numerical modeling can instantaneous response with qualified accuracy. The proposed method can contribute to independently zonal environment control and occupant-centered micro-environment control.

Validation of Ablation and Thermal Response Model for Three-Dimensional Multifunctional Ablator

A semi-empirical physics-based ablation and thermal response model was developed for the 3-Dimensional Multifunctional Ablative Thermal Protection System (3D-MAT) material. Model validation was achieved through comparison between computation and available data obtained in the arc-jet test series, which were conducted at NASA Ames Research Center from 2014 to 2020. The charring ablator simulations for arc-jet test models presented in this work were computed by the Two-Dimensional Implicit Thermal Response and Ablation (TITAN) code, and the Data-Parallel Line Relaxation Method (DPLR) code was used for arc-jet flow simulations to estimate the arc-jet stream total enthalpy and define the aerothermal boundary conditions over the test model surface for TITAN simulations. Because of low surface catalytic efficiency of 3D-MAT char, the exact surface heating could not be determined. Thus, three different types of boundary conditions, including 1) fully catalytic surface heating, 2) noncatalytic surface heating, and 3) surface temperature and recession, were used in the TITAN simulation for model validation. The predicted surface and in-depth temperature history for arc-jet test models were compared with pyrometer and thermocouple data, and the predicted test model surface recession and char depth were compared against the posttest measurements.

Modeling and validation of ablative thermal response combined with microscopic heat transfer for porous ablative materials

Porous ablative materials are the state-of-the-art thermal protection materials for extreme aerodynamic conditions during re-entry, but the precise analysis of heat transfer within microstructure and the ablative thermal response process is still a challenge. Herein, a numerical model that combines macroscopic ablative thermal response and microscopic heat transfer for porous ablative materials is presented. The microscopic heat transfer in the model is implemented through the conjugate solid and gas phases heat transfer. The model is validated by comparing the results of typical ablation cases with predictions made using another computational program PATO. In addition, analysis is performed to investigate the effect of parameters in the model such as thermal conductivity, heat capacity, surface emissivity, reaction kinetic parameters, and pressure. The results show that surface radiation is the majority of energy consumption mechanisms, and the internal temperature distribution of materials is primarily governed by thermal conductivity and heat capacity. Moreover, pressure serves as both the independent and dependent variable of thermal response, and the heat dissipation effect of pyrolysis gas exhibits a significant increase when it exceeds 10 atm. The results can improve the understanding of the ablative thermal response process and highlight areas for optimizing the design of TPS materials.

Performance analysis and comparison of data-driven models for predicting indoor temperature in multi-zone commercial buildings

Building thermal models, which characterize the properties of a building’s envelope and thermal mass, are essential for accurate indoor temperature and cooling/heating demand prediction. Because of their flexibility and ease of use, data-driven models are increasingly used. This study compared and analyzed the performance of gray-box (resistance-capacitance) and black-box (recurrent neural network) models for predicting indoor air temperature in a real multi-zone commercial building. The developed resistance-capacitance model served as a benchmark model for which full sets of temporal data and building information were used as inputs. The recurrent neural network models were trained and tested assuming various available types and amounts of temporal data and known building physical information to investigate the effects of data and information availability. Feature importance analysis was conducted to select the key variables for different prediction targets under different scenarios. This research provides guidance in selecting an appropriate building thermal response modeling method based on the measured data availability, building physical information, and application.

Improved solid radiation model for thermal response in large crude oil tanks

In a crude oil tank farm, a fire in a large crude oil storage tank can spread to its neighbouring tanks due to thermal radiation causing wall rupture. To better understand the thermal radiation of tank fires and the thermal response of their neighbouring tanks, a semi-empirical radiation model is proposed in this paper. The model takes into account the smoke generation and its effect in reducing thermal radiation, as well as the variation of flame temperature and emissivity along the flame axis. Compared with existing models, the model is able to predict the radiant heat flux of the flame more accurately, and this advantage becomes more pronounced as the diameter of the pool fire increases.Using the improved model, the effect of different crude oil contents on the thermal response and failure time of the storage tank under the action of thermal radiation was innovatively explored by numerical simulation. An in-depth analysis of the failure time was performed, and an empirical equation was derived to provide a reference for fire emergency management of large storage tanks.

Computational modelling and statistical evaluation of thermal runaway safety regime response on lithium-ion battery with different cathodic chemistry and varying ambient condition

As one of the most promising energy storage mediums, Lithium-ion batteries (LIBs) have attracted extensive research interest. A major challenge associated with LIB application is thermal runaway, which can be triggered under abused conditions and impose direct threats to life and properties. Thermal runaway is a major source of fire and explosions in the battery energy storage industry. In this paper, the thermal runaway numerical model is used to explain the evolution of thermal runaway trigger point over different cathodic chemistry under the influence of varying ambient temperature. The test is performed using nail penetration assisted thermal abuse method. The model is based on the conservation of energy Equation, with the empirical corelation of the thermal abuse equations which is used to simulate the source term. Additionally, experimental literature is used to verify the simulation results extensively. The simulation results are utilized to monitor internal short circuit circumstances that lead to the thermal runaway trigger point, and a comparison scaled map is created between various chemistry to show which chemistry triggers prematurely between LiNiMnCoO2 (NMC), LiFePO4 (LFP), and LiCoO2 (LCO). The existing critical uncertainty, such as nail diameter, heating profile, variation in operating ambient temperature, battery jelly roll thickness and effect of convective parameters is investigated in detailed and decision tree is prepared using ANOVA statistical method.

Thermal response modeling and analysis of hydrocarbon fuel transient flow and heat transfer at supercritical pressure

The demands for wider speed range and longer endurance of hypersonic vehicles make the flight state transition an issue to be considered. To get a fundamental understanding of the thermal response characteristics of supercritical fuel under varying operation conditions, a series of experimental and numerical studies have been conducted in this research. The effects of different operation parameters on the response time have also been investigated. The research revealed that when the temperature is below the pseudo-critical temperature, the thermal response time decreases with the increase of temperature. Additionally, the results have shown that the mass flow rate increase leads to the decrease of thermal response time decreases in the same temperature range. The effect of pressure is most notable near the pseudo-critical temperature due to the drastic change of physical properties near the pseudo-critical temperature. The effect of the solid domain on the response time is accomplished through the thermal conduction in the solid domain, and a thicker wall thickness and higher thermal inertia of the tube lead to a longer response time. An empirical correlation based on the experimental data has been proposed to predict the thermal response time. These results provide a reference for cooling channel design and coolant management.

Analytical workload dependence of self-heating effect for SOI MOSFETs considering two-stage heating process

Dynamic self-heating effect (SHE) of silicon-on-insulator (SOI) MOSFET is comprehensively evaluated by ultrafast pulsed I–V measurement in this work. It is found for the first time that the SHE complete heating response and cooling response of SOI MOSFETs are conjugated, with two-stage curves shown. We establish the effective thermal transient response model with stage superposition corresponding to the heating process. The systematic study of SHE dependence on workload shows that frequency and duty cycle have more significant effect on SHE in first-stage heating process than in the second stage. In the first-stage heating process, the peak lattice temperature and current oscillation amplitude decrease by more than 25 K and 4% with frequency increasing to 10 MHz, and when duty cycle is reduced to 25%, the peak lattice temperature drops to 306 K and current oscillation amplitude decreases to 0.77%. Finally, the investigation of two-stage (heating and cooling) process provides a guideline for the unified optimization of dynamic SHE in terms of workload. As the operating frequency is raised to GHz, the peak temperature depends on duty cycle, and self-heating oscillation is completely suppressed.

Peridynamic modeling of thermal response and cracking in charring materials due to ablation

Peridynamic modeling of thermal response and cracking in charring materials due to ablation

A Crack Detection Method for Aero-engine Blade Based on Air-Flow Thermography

Aero-engine blade is one of the core components of aero-engine and its safe service is crucial to the normal operation of aero-engine. Thus, it is very important to localize and quantify cracks of aero-engine blades to prevent safety accidents. To guarantee the structural health of aero-engine blades, the air-flow thermography (AFT) method which has advantages of non-contact, high performance, and sensitivity, was proposed for detection of the blade cracks. Firstly, the theoretical thermal response model was established and the crack simulation models with different depths were constructed. Then a detection system was established to detect the artificial cracks with different depths and orientations. Results showed that the proposed method can effectively quantify the cracks with different depths from 0.2 mm to 1.0 mm and characterize the crack orientations. In addition, the natural crack on the blade was detected and the principal component analysis (PCA) method was used to enhance the crack contrast with the background.

Thermal stability of emerging N6-type energetic materials: kinetic modeling of simultaneous thermal analysis data to explain sensitivity trends.

A number of new high-performing energetic materials possess explosophoric functionalities, high nitrogen content, and fused heterocyclic blocks. Two representatives of these materials have been synthesized recently, namely, 1,2,9,10-tetranitrodipyrazolo[1,5-d:5',1'-f][1,2,3,4]-tetrazine (1) and 2,9-dinitrobis([1,2,4]triazolo)[1,5-d:5',1'-f][1,2,3,4]tetrazine (2). The thermal stability of these energetic materials bearing the N-N-N = N-N-N fragment and three closely related compounds has been investigated for the first time. The thermal decomposition process of analyzed compounds was complicated by the appearance of the liquid phase, sublimation of the material, and autocatalysis by reaction products. In contrast to the traditional approach to the kinetic modeling based on data from either TGA or DSC, we use both signals' data measured at the same time and perform the joint kinetic analysis using the model-fitting technique to obtain the pertinent kinetic description of the process. Of the analyzed materials, 1 and 2 show the lowest thermal stability in melt with a characteristic rate constant of 2.6 × 10-3 s-1 at 250 °C. The kinetic parameters and calculated detonation performance data were used in the model to describe the mechanical sensitivity. The model output and the experimental friction sensitivity data show a respectable agreement, but more data are required to draw firm conclusions. In general, the provided thermal stability and kinetic data can be used for thermal response and storage modeling of these new N6-type energetic materials. The developed thermokinetic approach, joint model-fitting of several thermal analysis signals, can be applied to other complex thermally induced processes to increase the value and credibility of the kinetic findings.

Heat transfer and pyrolysis gas flow characteristics of light-weight ablative thermal protection system in the blunt body

Thermal protection system (TPS) is the critical system to protect the structure and electronic components of hypersonic vehicles from aerodynamic heating. Since the blunt body suffers the most severe thermal environment in a flight vehicle, the design of TPS for the blunt body is crucial. To investigate the thermal performance of the light-weight ablative material in the blunt body, a multi-dimensional thermal response model is proposed considering heat transfer, pyrolysis gas flow, and gas blowing effect. The characteristics of heat diffusion, pyrolysis process, gas flow, and the effect of pyrolysis gas blowing are investigated. It shows that the developed model can accurately predict temperature and gas flow. The temperature and charred thickness at the stagnation point are the largest, decrease along the surface of the sphere nose, and keep almost the same at the cone. Due to the surface pressure distribution, a large part of the pyrolysis gas in the sphere nose flows through the ablative material and injects into the air at the sphere-cone junction. In contrast, the gas at the cone flows vertically to the cone surface. The gas flow rate and pressure decrease as time elapses. Moreover, gas blowing mainly influences the thermal response near the sphere-cone junction, leading to a minimum blowing factor of 0.965 and a max temperature reduction of 7.4% at 100s. The effect of gas blowing is enhanced with the increase of phenolic resin content. This study deepens the understanding of the thermal performance of light-weight ablative material in the blunt body and guides the ablative thermal protection design.