Surface Temperature Measurements Research Articles

How birds dissipate heat before, during and after flight.

Animal flight uses metabolic energy at a higher rate than any other mode of locomotion. A relatively small proportion of the metabolic energy is converted into mechanical power; the remainder is given off as heat. Effective heat dissipation is necessary to avoid hyperthermia. In this study, we measured surface temperatures in lovebirds (Agapornis personatus) using infrared thermography and used heat transfer modelling to calculate heat dissipation by convection, radiation and conduction, before, during and after flight. The total non-evaporative rate of heat dissipation in flying birds was 12× higher than before flight and 19× higher than after flight. During flight, heat was largely dissipated by forced convection, via the exposed ventral wing areas, resulting in lower surface temperatures compared with birds at rest. When perched, both before and after exercise, the head and trunk were the main areas involved in dissipating heat. The surface temperature of the legs increased with flight duration and remained high on landing, suggesting that there was an increase in the flow of warmer blood to this region during and after flight. The methodology developed in this study to investigate how birds thermoregulate during flight could be used in future studies to assess the impact of climate change on the behavioural ecology of birds, particularly those species undertaking migratory flights.

A Warming Southern Gulf of Mexico: Reconstruction of Anthropogenic Environmental Changes From a Siderastrea siderea Coral on the Northern Coast of Cuba

AbstractThe Gulf of Mexico is a vital region for the Atlantic Meridional Overturning Circulation (AMOC), that fuels the exchange of heat between the tropics and the polar regions. A weakening of the AMOC would have dire consequences for the planet. First observations and ocean models show that this process has already started. Very limited knowledge of the components that are part of the AMOC such as the Loop Current (LC) make it difficult to understand its dynamics as well as changes in strength or temperature since the onset of the Industrial Revolution. Currently, there are no continuous in situ sea surface temperature or salinity measurements for the southeastern Gulf of Mexico or reconstruction attempts for this region, showing the necessity for high‐resolution climate archives. A Siderastrea siderea coral core was retrieved from the northwestern Cuban coast and used as a sub‐seasonally resolved sea surface temperature and hydroclimate archive. The approach is based on skeletal δ18O, and trace and minor element contents show an increase in temperature over 160 years since 1845 of 2.6–3.3°C. A possible stagnation of the warming trend set in after the 1980s, indicating a potential weakening of the Loop Current. Impacts in sea surface salinity such as El Niño events in the Pacific region can still be detected in the Gulf of Mexico as decreases in salinity in 1998 from the reconstructed δ18OSW coral record. In situ measurements remain crucial to understand the dynamics in the LC and its influence on the AMOC.

Investigating Dynamic Weakening in Laboratory Faults Using Multi‐Scale Flash Heating Coupled With mm‐Scale Contact Evolution

AbstractFlash‐weakening models typically show good agreement with the total magnitude of weakening in high‐speed rock friction experiments, however deviations during the acceleration and deceleration phases, and at low and intermediate sliding velocities, remain unresolved. Here, we incorporate inhomogeneous mm‐scale normal stress evolution into a model for flash heating and weakening to resolve outstanding transient and hysteretic friction observed in laboratory experiments and to identify unique solutions to constitutive parameters. We conduced 37 rock friction experiments on Westerly granite using a high‐speed biaxial apparatus outfitted with a high‐speed infrared camera. We initiated velocity steps from quasi‐static rates of 1 mm/s to sliding velocities ranging from 300 to 900 mm/s and conducted both constant‐ and decreasing‐velocity tests following the velocity step. Two sliding surfaces geometries were used to control mm‐scale life‐times and rest‐times. Constant‐strength sliding is achieved within 2–3 mm of initiating the velocity step in all constant‐velocity experiments. Macroscopic surface temperature is inhomogeneous and increases with slip distance, velocity, and decreasing rest‐time. Weakening increases with sliding velocity and decreasing rest‐time. We combine thermal models with measured surface temperatures to constrain the evolution of local normal stress at the mm‐scale and incorporate this evolution into a flash‐weakening model that considers weakening at both the µm‐ and mm‐scale. The flash‐weakening model improves when the effects of mm‐scale wear processes are incorporated and multi‐scale weakening is considered, however some transient friction remains undescribed. Models will be advanced by further incorporating wear processes and by considering processes at the mm‐scale and above.

A Neural Network-Based Method for Real-Time Inversion of Nonlinear Heat Transfer Problems

Inverse heat transfer problems are important in numerous scientific research and engineering applications. This paper proposes a network-based method utilizing the nonlinear autoregressive with exogenous inputs (NARX) neural network, which can achieve real-time identification of thermal boundary conditions for nonlinear transient heat transfer processes. With the introduction of the NARX neural network, the proposed method offers two key advantages: (1) The proposed method can obtain inversion results using only surface temperature time series. (2) The heat flux can be estimated even when the state equation of the system is unknown. The NARX neural network is trained using the Bayesian regularization algorithm with a dataset comprising exact surface temperature and heat flux data. The neural network takes current and historical surface temperature measurements as inputs to calculate the heat flux at the current time. The capability of the NARX method has been verified through numerical simulation experiments. Experimental results demonstrate that the NARX method has high precision, strong noise resistance, and broad applicability. The composition of the input data, the surface temperature measurement noise, and the boundary heat flux shape have been studied in detail for their impact on the inversion results. The NARX method is a highly competitive solution to inverse heat transfer problems.

Development, implementation, and impact analysis of model predictive control-based optimal precooling using smart home thermostats

Model Predictive Control (MPC)-based precooling strategies are typically analyzed through simulations. Their field studies in residential buildings are quite limited due to hardware retrofitting costs, lengthy parameter identification periods, and the need to have homeowners' participation. Therefore, there is a lack of MPC-based precooling impact analysis using field data which may have prevented widespread adoption of the technology. To address this issue, in this paper we developed an MPC agent and implemented it on an online cloud-based platform. The MPC agent makes use of a gray-box model to capture the home thermal dynamics, a novel set of constraints to ensure that the model parameters identified are realistic, and a node sensor to provide interior wall surface temperature measurement. To evaluate its performance and conduct impact analysis, we introduced a modified matrix profile-based weather clustering algorithm and two performance indicators for cost saving and energy flexibility. We also carried out extensive field tests on nine homes over a period of four months. Our results show that the MPC agent can reduce energy cost by 28.72%–51.31% on hot summer days and by up to 60.32% on mild summer days, in addition to achieving significant energy flexibility. Moreover, the agent's performance is found to be most impacted by weather conditions, AC performance, user comfort preferences, and floor areas of the homes.

Quantifying Part-to-Part Flow Variations and Cooling Effectiveness in Engine-Run Blades

Abstract As turbine inlet temperatures continue to increase for modern gas turbine engines, the lifing of hot section components operating in a range of environments is becoming increasingly challenging. Engine operations in harsh environments can cause a reduction in cooling capability leading to reduced blade life relative to existing experience. This study analyzes the effects of harsh environments on the deterioration of blade flow and cooling effectiveness in turbine blades by comparing three commercially operated engines with varied operational times referenced against a baseline blade. Spatially resolved surface temperatures measured using infrared thermography at high-speed rotating conditions were evaluated to determine variations in cooling effectiveness as a function of engine operation and blade-to-blade variability from the different commercial applications. Engine-run blades were found to have reduced flow as well as greater part-to-part variation when compared to baseline blades. Blade surface temperature measurements on the deteriorated operational blades indicated film cooling traces dissipated closer to the hole exit relative to baseline blades. Furthermore, the cooling effectiveness varied significantly even between blades from the same engines. The reduction in cooling effectiveness in the engine-run blades led to higher blade temperatures and significantly shorter component life, with some exhibiting as much as an 18% reduction in life compared to baseline blades. This knowledge allows lifing models to be developed toward predicting blade operational effects in harsh environments.

The Evaluation of the Temperature Reduction Effects of Cool Roofs and Cool Pavements as Urban Heatwave Mitigation Strategies

Various types of damage, including health risks, caused by abnormal climate conditions have gradually increased in recent years, particularly in cities with a high degree of complexity. In particular, it is important to address heatwave damage risk from both technical and policy perspectives because it poses risks to older adults and/or disadvantaged individuals. This study was performed to assess the quantitative effects of two heatwave mitigation measures, cool roofs and cool pavements, in the Jangyumugye district of Gimhae, Republic of Korea. Thermal imaging cameras were used to measure surface temperatures after the installation of these measures; after the installation of cool roofs, indoor temperatures were also measured using temperature measurement data loggers. Then, a survey was conducted to obtain feedback from users of the associated facilities. From August to October 2019, surface temperatures were significantly reduced following the installation of cool roofs and cool pavements. Cool roofs constructed using slabs and panels provided average temperature reductions of 15.5 °C and 11.6 °C, respectively. Cool pavements showed a temperature reduction of ≥4 °C in both parking lot and alley sites. More than 30% of users noticed a reduction in temperature as a result of heatwave measure installation. These results may be used by the city to make informed policy decisions regarding the implementation of heatwave mitigation measures.

An adaptive threshold method for multi-faults diagnosis of lithium-ion batteries based on electro-thermal model

Lithium-ion batteries have emerged as the primary power source for electrochemical energy storage, making battery safety a crucial concern. This study focuses on the detection of thermal faults in lithium-ion batteries, specifically heat generation faults, thermal parameter faults, and temperature sensor faults. To address the issue of low accuracy in temperature indirect estimation models, a framework that combines electrical and thermal models is proposed. This framework employs particle swarm optimization to identify optimal thermal model parameters using real-time open circuit voltage and terminal voltage data. Additionally, an unscented Kalman filter estimator is utilized to predict core temperature based on surface temperature measurements in real time. The results demonstrate that the proposed framework achieves rapid convergence of core and surface temperature biases within a range of 1 ℃ and 0.1 ℃, respectively. Furthermore, an adaptive threshold method is developed to diagnose faults by analyzing the change rates of the estimated temperatures. Experimental results reveal that the proposed methods exhibit quick response times for four different fault conditions, indicating their effectiveness and accuracy in multi-fault diagnosis.

Modeling Slope Microclimates in the Mars Planetary Climate Model

AbstractA large number of surface features (e.g., frost, gullies, slope streaks, recurring slope lineae) are observed on Martian slopes. Their activity is often associated with the specific microclimates on these slopes, which have been mostly studied with one‐dimensional radiative balance models to date. We develop here a parameterization to simulate these microclimates in 3D Global Climate Models. We first demonstrate that any Martian slope can be thermally represented by a poleward or equatorward slope, that is, the daily average, minimum, and maximum surface temperatures depend on the North‐South component of the slope. Based on this observation, we implement here a subgrid‐scale parameterization to represent slope microclimates (radiative fluxes, volatile condensation, ignoring slope winds for now) in the Mars Planetary Climate Model and validate it through comparisons with surface temperature measurements and frost detections on sloped terrains. With this new model, we show that slope microclimates do not have a significant impact on the seasonal CO2 and H2O cycles on a global scale. Furthermore, short‐scale slopes (i.e., less than ∼1 km in length) do not significantly impact the thermal state of the atmosphere. Ninety‐one percent of the active gullies are found where our model predicts CO2 frost, suggesting that their activity is related to processes involving CO2 ice. However, the low thicknesses (≤tens of cm) predicted at mid‐latitudes rule out mechanisms involving large amounts (∼meters) of ice. This model opens the way to new studies on surface‐atmosphere interactions in present and past climates.

Prediction of Isotropic Rough Surface Directional Spectral Emissivity with Surface-Morphology-Dependent Modelling

The surface directional spectral emissivity of rough metal surfaces in industry is of concern in infrared temperature measurement. In this research, the height and slope possibility density functions are introduced as variables, and the directional spectral emissivity of isotropic rough surface is modelled accordingly. The model is designed to derive the directional spectral emissivity of rough metal surfaces from the surface morphology (possibility distribution of the height and slope) and the material property parameters (refractivity). Then, a sandblasted surface is taken as a case study. The sandblasted surface morphology is measured. A Polynomial surface is proposed to describe the sandblasted surface morphology and is compared with a Gaussian surface and a Cox–Munk surface. Finally, the directional spectral emissivity measurement and infrared temperature measurement are conducted. It is shown that the predicted directional spectral emissivity and measured temperature with the surface-morphology-dependent isotropic rough surface directional spectral emissivity model have high precision. In this work, the possibility distribution of the height and slope of the surface is introduced as independent variables to provide better accuracy compared to the reported models. In some cases, the error of the infrared temperature measurement could be reduced to 20% (80 degrees, compared to Gaussian surface). This work contributes to improving the accuracy of IR temperature measurement of rough surfaces.

Assessing aerobic physical efficiency through temple surface temperature measurements during light, heavy exercise, and recovery

The study was conducted to determine thecorrelation between the selected measures of aerobic physical efficiency and changes in the temple surface temperature in response to light and heavy exercise. 25 physically active men aged 19–25 were recruited for the study. They performed a graded exercise test on a cycle ergometer to measure maximum power (Pmax) and a test verifying the value of maximum oxygen uptake (VO2max). Then, two 3-min submaximal efforts with constant-intensity of 2.2 W·kgLBM−1 and 5 W·kgLBM−1, respectively were performed. During the constant-intensity efforts, the temperature of the temple surface was measured. Then, the difference between the temperature of the temple measured at the end of the exercise and the temperature measured at the beginning of the exercise was calculated (ΔT1-2.2, ΔT1-5, respectively). It was shown that ΔT1-2.2 correlated statistically significantly with VO2max (ml·min−1·kg−1) (r = 0.49; p = 0.01) and Pmax (W·kg−1) (r = 0.41, p = 0.04). Moreover, ΔT1-5 correlated statistically significantly with VO2max (l·min−1) (r = − 0.41; p = 0.04). Changes in body surface temperature in response to light exercise positively correlate with measurements of aerobic physical efficiency, such as VO2max and Pmax. When the exercise intensity is high (5 W·kgLBM−1), the correlation between exercise body temperature changes and VO2max becomes negative.

Development of multi-spectral pyrometer for measuring cathode surface temperature of pulsed vacuum arc discharge

The cathode surface temperature is a vital parameter in the pulsed vacuum arc discharge process, which has an important influence on the formation of vacuum arc plasma, electrode corrosion prediction and ion source lifetime. Currently, the research of cathode surface temperature measurement is mainly based on a high-speed charge coupled instrument (CCD) camera. However, there are no other temperature measuring instruments to verify the results of a high-speed camera. For this reason, a new type of multi-spectral pyrometer is developed. The developed pyrometer adopts optical filter instead of traditional prism splitting, which simplifies the calibration process of pyrometer. An optical sampling system is redesigned to ensure that a tiny target of 100 μm can be measured. On the built experimental platform, the synchronous experiment of multi-spectral pyrometer and high-speed camera are carried out. The experimental results show that the developed multi-spectral pyrometer can verify the measurement results of the multi-spectral pyrometer based on high-speed camera.

Impact of Giant Iceberg A68A on the Physical Conditions of the Surface South Atlantic, Derived Using Remote Sensing

AbstractGiant icebergs release cold, fresh meltwater as they drift, perturbing the physical conditions of the surface ocean. This study uses satellite‐derived sea surface salinity and temperature measurements to explore the physical impact of supergiant iceberg A68A between September 2020 and June 2021. During A68A's drift through the Scotia Sea in austral spring, gradual but persistent edge‐wasting contributed to a freshening of several psu extending hundreds of kilometers ahead of the iceberg, whilst the cooling signal was more pronounced in the iceberg's wake. The magnitude of the physical perturbation intensified during A68A's breakup near South Georgia. Several large meltwater lenses surrounding the descendant icebergs displayed temperature anomalies of up to −4.5°C, whilst the salinity measurements indicated a surface (skin‐depth) anomaly regularly exceeding order −10 psu. The perturbations stretched at times >1,000 km and persisted for >2 months following A68A's melt in April 2021.

Hypergolic ignition response to oxidizer droplet properties

The hypergolic ignition response to oxidizer droplet properties is an important consideration for oxidizer injector design in hybrid rocket motors. Hence, the present work focused on hypergolic ignition characterization as a function of droplet properties and impact dynamics for a promising propellant. The propellant for the present work consisted of rocket grade hydrogen peroxide (RGHP) as oxidizer, high-density polyethylene (HDPE) as fuel and sodium borohydride (NaBH4) as the hypergolic additive embedded in the HDPE matrix. This propellant was chosen for this detailed study since it showed promising results in prior studies, exhibiting low (<10 ms) ignition delays. For this work, in a drop-test setup, RGHP droplet diameters between 1.90±0.11 mm and 4.35±0.26 mm were dropped on the HDPE + NaBH4 fuel samples at velocities between 0.3 m/s to 1.93 m/s. The ensuing ignition event was studied using both visible and infrared high-speed imaging. Post-impact droplet parameters were determined to enable a deeper analysis of observed phenomena. While ignition delay was the focus of this work, flame spread areas and heat release were also studied. Higher impact velocities generally led to lower ignition delays while splashing oxidizer drops increased probability of larger flame areas and higher heat release. Additionally, the initial ignition/heat release event was found to originate in a small region at the thinnest area of the post-impact droplet. Surface temperature measurements were also performed using infrared imaging. The data suggested that the initial heat release was found to be likely due to RGHP-NaBH4 reaction with no contribution from RGHP decomposition. Regression and random forest machine learning analysis found ignition delay depended strongly on the minimum post-impact drop layer thickness. Based on the data analysis, a simple mathematical model was developed whose results matched experimentally observed trends. The study is expected to further understanding of the processes that control hypergolic ignition in addition to aiding rocket engineers design better oxidizer feed systems. Novelty and SignificanceThis work constitutes a novel in-depth study on the influence of drop impact properties on hypergolic ignition. Using innovative techniques, this work is the first to show the overwhelming importance of residual droplet layer thickness on ignition delay. Additionally, a simple mathematical model based on that finding performed well against experimental data which is of substantial significance, given the complex and multi-parametric nature of hypergolic ignition. Finally, the work establishes that operating in the splashing regime enhances heat release and flame spread. The candidate propellant for this work was hydrogen peroxide and high-density polyethylene with embedded NaBH4. However, the findings of this study are likely generalizable over a range of solid-liquid hypergolic propellants involving solid fuels with embedded energetic materials, of which there are many. The findings of this work can enhance understanding of hypergolic ignition in addition to aiding in better rocket injection system design.

Lunar grain size determination based on surface temperatures using ensembles of thermal model parameters

Surface temperature measurements of airless bodies provide an opportunity to estimate regolith thermal properties via inverse modeling. However, thermal models involve many unknown parameters. Here an ensemble of thermal model calculations is applied to lunar nighttime surface temperatures in order to constrain the mean particle size of near-surface regolith materials. We find that many parameter combinations can produce the same surface temperatures, but a likely apparent grain size can be inferred without ad-hoc assumptions for other parameter values as long as grain size is among the leading causes for geographic variations in temperature.

Data Reconstruction of Sea Surface Temperature in Indonesia’s Fish Management Area 713 (IFMA-713) Using Machine Learning

The IFMA-713 in Indonesia is water that has dynamic of temperature changes due to interactions with the Pacific Ocean and the surrounding. Sea surface temperature data can be obtained by measuring with satellite imagery. However, satellite imagery measurements of sea surface temperature can be incomplete due to cloud cover. In this study, a machine learning method was used to reconstruct sea surface temperature data using a backpropagation neural network algorithm. The data used in this research is data captured with MODIS Satellite. Then, the reconstruction of sea surface temperature data is carried with four scenarios with missing data percentages: empty data, zero values, average values at the point of data collection, and Indonesia’s average sea surface temperature. Accurate results were obtained in reconstructing sea surface temperature where the scenarios had a positive correlation. The most accurate scenarios for reconstructing sea surface temperature data with missing data were those in which the empty data was filled with average values at the point of data collection or Indonesia’s average sea surface temperature.

Effect of Pressure and Turbulence Intensity on the Heat Flux During Flame Wall Interaction (FWI)

Combustion applications such as internal combustion engines are a major source of power generation. Renewable alternative fuels like hydrogen and ammonia promise the potential of combustion in future power applications. Most power applications encounter flame wall interaction (FWI) during which high heat losses occur. Investigating heat loss during FWI has the potential to identify parameters that could lead to decreasing heat losses and possibly increasing the efficiency of combustion applications. In this work, a study of FWI (CH4-air mixture) in a constant volume chamber, with a head-on quenching configuration, at high pressure in both laminar and turbulent conditions is presented. High-speed surface temperature measurement using thin junction thermocouples coupled with high-speed flow field characterization using particle image velocimetry (PIV) are used simultaneously to investigate the effect of pressure during FWI (Pint) and turbulence intensity (q) on the heat flux peak (QP). In laminar combustion regimes, it is found that QP is proportional to Pint0.35. The increase in q is shown to affect both Pint and QP. Finally, comparing QP versus Pint for both laminar and turbulent combustion regimes, it is found that an increase in q leads to an increase in QP (b = 0.76).

Remote sensing‐based geostatistical hot spot analysis of Urban Heat Islands in Dhaka, Bangladesh

Urban Heat Island (UHI) refers to a phenomenon whereby urban areas experience higher temperatures compared to the surrounding areas. Remote sensing‐based Land Surface Temperature (LST) measurements can be utilized to measure UHI. This study emphasized on geostatistical remote sensing‐based hot spot analysis () of UHI in Dhaka, Bangladesh as a way of examining the influences of Land Use Land Cover (LULC) on UHI from 1991 to 2015. Landsat 5 and 7 satellite‐based remote sensing indices were used to explore LULC, UHI and environmental footprints during the study period. The Urban Compactness Ratio (CoR) was used to calculate the urban form and augmented characteristics. The Surface Urban Heat Island (SUHI) intensity (ΔT) was also used to explore the effects of UHI on the surrounding marginal area. Based on our investigations into LULC, we discovered that around 71.34 per cent of water bodies and 71.82 percent of vegetation cover decreased from 1991 to 2015 in Dhaka city. Contrastingly, according to CoR readings, 174.13 km2 of urban areas expanded by 249.77 per cent. Our hot spot analysis also revealed that there was a 93.73 per cent increase in hot concentration zones. Furthermore, the average temperature of the study area had increased by 3.26°C. We hope that the methods and results of this study can contribute to further research on urban climate.

Tb3+/Mn4+ co-doped SrLaMgNbO6 green/red dual-emitting phosphors for optical thermometry

Remote and noncontact surface temperature measurements are frequently required yet challenging to execute. One the most promising options consists in using rare earth or transition metal doped materials as optical (luminescence) temperature sensors. In this paper, a series of novel Tb3+/Mn4+ co-doped SrLaMgNbO6 (SLMN) phosphors have been synthesized and thoroughly investigated for their structural, luminescence spectroscopic and decay kinetics properties as well as for temperature sensing performance. X-ray powder diffraction (XRD) analysis has shown that the prepared sample presents a double perovskite structure. Upon the UV excitation, emission spectra of SLMN:Tb3+, Mn4+ exhibit green and red emission bands for Tb3+ and Mn4+ dopants, respectively. Temperature-dependent photoluminescence (TD-PL) studies revealed sever thermal quenching of Mn4+ emission while that of Tb3+ was moderate providing well pronounced difference in fluorescence intensity ratios (FIR) of the ions. The maximum relative sensitivity (Sr) was found to be 3.27% K−1 and 1.92% K−1 for Mn4+ and Tb3+, respectively. This implies that SLMN: Tb3+, Mn4+ phosphor is a viable candidate material for a dual-mode optical temperature detection.

A data-assimilative modeling investigation of Gulf Stream variability

An advanced data-assimilative ocean circulation model is used to investigate Gulf Stream (GS) variability during 2017–2018. The modeling system applies a strong-constraint, 4D variational data assimilation algorithm. It assimilates satellite-based sea surface height and sea surface temperature measurements and in situ temperature and salinity profiles. Model skill assessment metrics along with comparisons of GS position and GS's three-dimensional mean kinetic energy with historical observations are applied to validate the data-assimilative model. The resulting time- and space-continuous ocean state estimates are used to diagnose eddy kinetic energy conversion and cross-stream eddy heat and salt fluxes over the two-year study period. The processes leading to kinetic energy conversion are primarily due to GS meanders. Significant inverse energy cascading (EKE→MKE and EKE→EPE) can occur during GS-eddy interactions, particularly during onshore intrusions or offshore meanderings of the GS. Throughout the two-year study period, the cross-stream eddy heat and salt fluxes off Cape Hatteras were predominantly positive (onshore). Both GS offshore meandering (occurring 44% of the time and associated with shelf/slope water export) and GS intrusion (occurring 56% of the time) contribute to onshore heat and salt transport. Improved understanding of these processes and dynamics requires strong integration of an advanced observational infrastructure that combines remote sensing; fixed, mobile, and shore-based observing components; and high-resolution data assimilative models.