Surface Heat Flow Research Articles

Influences of heat flow on corrosion behavior and interfacial reaction kinetics

Heat transfer surface of heat exchange devices often suffers from severe corrosion, and their corrosion behavior is dramatically influenced by both surface temperature and heat flow. In this work, a novel heat transfer interface corrosion testing system was designed and built based on a simulation calculation analysis (COMSOL Multiphysics 6.0 software). By the aid of it, effects of different heat flux on corrosion performance of steel Q235 was investigated through mass loss and electrochemical methods in 0.5 mol/L H2SO4 solution at controlled interface temperatures. Results indicate that variations in concentration and temperature impose a great contribution to corrosion rate but not corrosion mechanism. However, heat flow not only changed the concentration of reactants near the interfacial surface but also affected the rate and kinetic mechanism of corrosion. Positive heat flow could reduce corrosion rate of heat transfer surface, while negative heat flow increased corrosion rate. Heat flow significantly altered parameters of the corrosion reaction rate constant (such as pre-exponential factor, activation energy, entropy change, and enthalpy change), and an approximate exponential relationship between corrosion rate and heat flux was proposed.

Deccan Volcanism and Related Seismic Unrest in the Koyna–Warna Region, India

Abstract Koyna–Warna is a region of low-tectonic deformation and normal surface heat flow (∼40 mW/m2) in the Deccan volcanic province, India, where low-to-moderate magnitude earthquakes have continued to occur in the last 60 yr. These earthquakes are uniquely restricted to an 11×16 km2 area and confined to the upper crust between 3 and 9 km depth. Located at the last phase of the interaction of India with the Reunion mantle plume ∼65 Ma ago responsible for extensive volcanism, the cause of sustained seismicity in Koyna region is debated. Using the shear-wave velocity model derived through the joint inversion of the receiver function and surface-wave data from the seismic zone, we propose that earthquakes in the Koyna region occur due to stress concentration arising because of the high-density magma intrusions in the shallow crust at 3–9 km. The high-density mafic-ultramafic body exerts gravitationally induced stress of about ∼12 to 15 MPa. The continuation of earthquakes in the deeper part is inhibited by the possible fluid-filled mush zone imaged as a low-velocity layer at a 9–17 km depth. The magma intrusion as dike can induce a cycle of normal faulting in the overlying rock mass, as observed in the Warna region. We present the first evidence of an extremely high velocity (>4.7 km/s) layer at 40–50 km below Moho, interpreted as the presence of eclogite–peridotite responsible for producing Deccan magma in large volume.

Deep thermal state on the southern margin of the Zhangzhou Basin based on the electrical conductivity model

Exploring the internal spatial and thermal structure of the Zhangzhou Basin is of great scientific significance in understanding the properties of the deep heat sources and the heating mechanism of hot springs in this region. This study estimates the temperature distribution within the upper mantle of the Basin's southern margin using the Arrhenius equation and Hashin-Shtrikman bounds based on a two-dimensional crust-mantle electrical resistivity model. We also employ a layered simulation technique to calculate the crustal temperature distribution using a one-dimensional steady-state heat conduction equation, constrained by the upper mantle's top and ground surface temperatures. This approach displays the characteristics of the longitudinal variations and horizontal inhomogeneities in crust-mantle temperature. Additionally, we estimate the heat flow values within the study area. Our findings reveal that: (i) the upper mantle (at depths of 30 - 50 km) exhibits a temperature range of 700 - 1100 °C, with the presence of local Moho and upper mantle uplifts; (ii) the crustal temperature spans from 21 - 900 °C, with a diminishing influence of the upper mantle uplift area on crustal temperature at shallower depths; (iii) the surface heat flow values derived from our simulations range between 87 and 100 mW/m2, averaging at 93.23 mW/m2; (iv) the exploration of dry heat rock in this region is likely to reach a depth of at least 6 km. These results suggest that the genesis of hot springs in the study area is not solely influenced by the heat energy extracted from large-area granitic surrounding rocks during a long transport process, but is also considerably affected by local deep thermal anomalous bodies and deep-large faults.

Characteristics and genesis of geothermal systems in the southern Junggar Foreland Basin, NW China

Complex structural styles of foreland basins and limited temperature data hinder our understanding of the characteristics and genesis of geothermal systems in these basins. Characteristics and genesis of the present thermal regime in the southern Junggar Foreland Basin are discussed and a conceptual model of the geothermal system is established based on steady-state temperatures, well-testing temperatures, thermal conductivities, radiogenic heat production, and thermal structures. Thermal conductivities of mudstone, sandstone, and volcanic rocks exhibit normal distribution patterns, with their average thermal conductivities in a consistent order. Heat production varies according to lithologic assemblages and uranium anomalies, being higher in mudstones and tuffs and lower in sandstones and coal measures. The geothermal characteristics are predominantly controlled by tectonic patterns, including geodynamic process and current basement structure. Surface heat flow is decreased from the first structural belts in the south to the third structural belts in the north and is converged from sub-depressions to sub-uplifts or anticlines, whose distribution matches well with positions of three structural belts. The generally low geothermal characteristics are attributed to thick thermal lithosphere and crust, as well as the thermal structure of “cold crust and cold mantle”. Groundwater and fault activities also influence heat flow. Additionally, uranium anomalies at the Cretaceous and Jurassic strata in the first structural belts enhance radiogenic heat production and result in continuously-distributed high heat flow. The heat generated by uranium anomalies helps explain the heat flow distribution in the first structural belts, which cannot be fully accounted for by tectonic-related thermal genesis alone.

The Distribution of Surface Heat Flow on the Tibetan Plateau Revealed by Data‐Driven Methods

AbstractSurface heat flow (SHF) serves as a vital parameter for assessing the heat transfer from deep Earth to the surface, which can provide crucial insights into internal geodynamic processes. As the “roof of the world,” the Tibetan Plateau and its tectonic evolution are highly important in terms of global climate change and geodynamic study. However, a comprehensive understanding of the SHF distribution across most regions of the Tibetan Plateau is limited due to sparse measurement data. To surmount this limitation, a spatially intelligent approach has been developed: The geographically neural network weighted regression with enhanced interpretability (EI‐GNNWR). This method integrates spatial heterogeneity and nonlinear interactions between geophysical and geological factors to predict the SHF distribution across the Tibetan Plateau. In this study, the EI‐GNNWR model is used to accurately predict SHF across the entire region. After evaluating the effectiveness and interpretability of the EI‐GNNWR model, our results demonstrate that medium to high SHF values are predominantly concentrated in the southern, northeastern, and southeastern sectors of the Tibetan Plateau. These observations suggest that the formation of zones with high SHF values may be strongly influenced by the Moho depth, ridges, topography, and average curvature of satellite gravity gradients. Especially, higher SHF values may indicate more profound geodynamic activities such as collisional orogeny, shear deformation zones, or lithospheric extension. These findings offer novel insights into the spatial patterns of SHF and deepen our understanding of the geothermal formation mechanisms driven by underlying tectonic activities.

JIRAM Observations of Volcanic Flux on Io: Distribution and Comparison to Tidal Heat Flow Models

AbstractJuno has allowed clear, high‐resolution imaging of Io's polar volcanoes using the Jovian Infrared Auroral Mapper (JIRAM) instrument. We have used data from JIRAM's M‐band (4.78 μm) imager from 11 Juno orbits to construct a global map of volcanic flux. This map provides short‐term insight into the spatial distribution of volcanoes and the ways in which high‐ and low‐latitude volcanoes differ. Using spherical harmonic analysis, we quantitatively compare our volcanic flux map to the surface heat flow distribution expected from models of Io's tidal heat deposition (summarized in de Kleer, Park, et al. (2019, https://doi.org/10.26206/d4wc‐6v82). Our observations confirm previously detected systems of bright volcanoes at high latitudes. Our study finds that both poles are comparably active and that the observed flux distribution is inconsistent with an asthenospheric heating model, although the south pole is viewed too infrequently to establish reliable trends.

Large-scale assessment of characteristic plant species on Eurasian saline and alkaline soda ecosystems

From an ecological standpoint, saline and alkaline habitats are considered as extreme environments for vascular plants because salinity and alkalinity serve as primary structuring factors that significantly influence the species richness of vegetation cover. The non-alkaline salinity stress on plants primarily results from interactions of NaCl, Na2SO4, and other neutral salts, whereas alkalinity stress is caused by NaHCO3 and Na2CO3, accompanied by an increase in pH. Some halophytes and salt-tolerant plants are well-adapted to such permanent abiotic stress. Surprisingly, they are able to survive and reproduce under environmental conditions of more than 200 mM NaCl concentration and are also able to live permanently in extreme conditions. The aim of this study was to identify characteristic and indicator plant species for permanently alkaline soda and non-alkaline saline wetland habitats, and to analyze the relationship between the chemical composition of water and the plant’s saturation index. Based on the obtained results we can conclude that plant species identified to live in high saline conditions may also grow under high alkaline conditions. Two groups were distinguished based on the salinity and alkalinity: “Saline group” includes all types of halophytes and halotolerant species, while “Soda group” includes obligate alkalophytes and alkalotolerant species. However, the diversity of plants in alkaline environment is bigger than in saline environment, and most of the halotolerant species grow in both alkaline soda and saline habitats. It is possible to identify three indicator species requiring alkaline soda habitats to live in (Aster tripolium, Puccinellia limosa, Suaeda pannonica) and three indicator species that dominantly grow in non-alkaline saline habitats (Juncus maritimus, Salicornia prostrata, Suaeda salsa). Different independent variables have been identified and analyzed to understand their influence on the species saturation index by calculating percentage of characteristic plant species of the entire region. It was identified that the plant saturation index has a significant positive relationship with the Mean Temperature of the Warmest Quarter, Topsoil Sand, and Clay fraction variables, and there is a significant negative relationship with the Solid Earth surface heat flow, as the heating can increase the extremity of the environment. Identification of indicator species of salinity and alkalization makes it possible to determine the type of soil, water bodies and habitats as a rapid biomonitoring method as a visual observation, without the use of expensive equipment and chemical laboratory tests.

Effects of winter climate parameters on the thermal performance of dynamic rotating latent-energy-storage envelope (DRLESE)

The accurate application of the Dynamic Rotating Latent-Energy-Storage Envelope (DRLESE) system necessitates careful consideration of outdoor climate conditions, which significantly impacted latent heat operation of Phase-Change Materials. The effects of climate parameters were explored by considering five convective heat transfer coefficients ranging from 10 W/(m·K) to 30 W/(m·K), six daily solar radiation intensities ranging from 15.0 MJ/Day to 30.0 MJ/Day, six air average temperatures ranging from −10.0°C to 15°C, and six fluctuation ranges of air temperature ranging from 5°C to 20°C. The thermal performance of the DRLESE system was evaluated by employing the liquid fraction of Phase-Change Materials (PCM), the thermal quantity of DRLESE, and the inner surface heat flow. The numerical results demonstrated that climate parameters have a profound effect on the thermal performance of the DRLESE system. Enhancing convective heat transfer coefficient or lowering outdoor air temperature can significantly attenuate thermal performance by promoting convective thermal dissipation, while increasing daily solar radiation intensity can provide ample solar radiation for absorption by the DRLESE system. With convective heat transfer coefficient increased from 10 W/(m2·K) to 20 W/(m2·K), the daily solar radiation intensity increased from 15MJ/Day to 30MJ/Day, outdoor air temperature increased from −10°C to 15°C, the fluctuation range increased from 5°C to 20°C, indoor effective thermal release was increased −55.38 %, 204.66 %, 241.00 % and 8.11 %, respectively. In addition, employing the transparent covers and selecting the appropriate PCM were recommended to enhance thermal performance of the DRLESE system.

Thermal Earth model for the conterminous United States using an interpolative physics-informed graph neural network

This study presents a data-driven spatial interpolation algorithm based on physics-informed graph neural networks used to develop a thermal Earth model for the conterminous United States. The model was trained to approximately satisfy Fourier’s Law of conductive heat transfer by simultaneously predicting subsurface temperature, surface heat flow, and rock thermal conductivity. In addition to bottomhole temperature measurements, we incorporated other spatial and physical quantities as model inputs, such as depth, geographic coordinates, elevation, sediment thickness, magnetic anomaly, gravity anomaly, gamma-ray flux of radioactive elements, seismicity, electrical conductivity, and proximity to faults and volcanoes. With a spatial resolution of 18km2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$18 \\ km^2$$\\end{document} per grid cell, we predicted heat flow at surface as well as temperature and rock thermal conductivity across depths of 0-7km\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0-7 \\ km$$\\end{document} at an interval of 1km\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1 \\ km$$\\end{document}. Our model showed temperature, surface heat flow and thermal conductivity mean absolute errors of 6.4∘C\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$6.4^\\circ C$$\\end{document}, 6.9mW/m2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$6.9 \\ mW/m^2$$\\end{document} and 0.04W/m-K\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0.04 \\ W/m-K$$\\end{document}, respectively. This thorough modeling of the Earth’s thermal processes is crucial to understanding subsurface phenomena and exploiting natural underground resources. Our thermal Earth model is available as web application at https://stm.stanford.edu, feature layers on ArcGIS at https://arcg.is/nLzzT0, and tabulated data on the Geothermal Data Repository at https://gdr.openei.org/submissions/1592.

Gravity field and geothermal structure of the Corsica‐Sardinia Block

AbstractThis paper presents a finite‐differences 3D numerical model that simulates the gravity and thermal structure of the Corsica‐Sardinia Block (CSB), an apparently stable lithospheric domain characterized by cryptic tectonic activity. In the experiments, we change the density and heat production rate of the model crust within a range of geologically realistic values to fit the measured Bouguer gravity anomaly and surface heat flow pattern. The discrepancy between the observed geophysical structure and the outcomes of numerical modelling are discussed in relation to the composition of the CSB crust and finally recast in the geodynamic framework of the western Mediterranean region.

Analysis on rotation timing of dynamic Rotating latent-energy-storage envelope (RLESE)

The application efficiency of the Dynamic Rotating Latent-Energy-Storage Envelope (DRLESE) system is highly contingent upon dynamic rotation timings. To gain the optimal rotation timings, six different timings were examined by employing the liquid fraction, thermal storage and release, surface temperature and heat flow. The numerical heat transfer method was employed and verified an experiment. Results indicated that the optimal initial rotation occurs in the forenoon, when the inner surface temperature aligns with the sol-air temperature. Subsequently, achieving optimal secondary rotation is possible in the afternoon when the sol-air temperature equals the liquid temperature of PCM (Phase Change Material). Under these optimized initial and secondary rotation timings, the significant enhancements in thermal performance of the DRLESE system were observed. By optimizing rotation timings, indoor effective heat release can reach up to 3182.9 kJ/Day with an effectiveness percentage exceeding 99.99%, and inner surface heat flow was increased by 5.86%–12.26%.

Predicting heat flow in the Iranian plateau and surrounding areas based on machine learning approach

While Surface Heat Flow (HF) is an important constraint unveiling the Earth interior's thermal structure, estimates over the Iranian plateau are sparse. In the presence of sparse estimates, machine learning provides a statistical-based prediction of HF based on a supervised predictor trained in the far-field regions. Here, we imply the machine learning technique of Gradient Boosting Regression Tree (GBRT) which has been proved to be efficient for predicting HF projecting complexities and nonlinearities of input features into predicted HF. Our results provide a robust map of HF with resolution of one degree and uncertainty of up to ±6 mW/m2 over Iran and surrounding regions. The predicted HF has an average value and minimum standard deviation of 59 and 10 mW/m2, respectively. The quality of the algorithm performance is 16%, indicated by normalized Root-Mean-Square Error (RMSE), and linear correlation of predicted HF with validation set is 97%. Total number of trees considerably prevents overfitting which is believed to be solely controllable by shrinkage factor, maximum tree depth and cross-validation scheme. The three most important features, having the highest influence on the output HF, are thermal Lithosphere-Asthenosphere Boundary (LAB), distance to volcanoes and distance to trenches. The extreme importance of LAB in HF prediction of Iran indicates that the lithospheric thermal structure is significantly controlled by lithospheric thickness in the Iranian plateau. Selection of petrologically and seismologically consistent LAB guarantees the precision of the predicted HF. Our results imply that high HF in central Iran is in agreement with extensive magmatism since the Paleozoic. Additionally, the high HF in Zagros keel (originally Proterozoic as the Zagros keel appears to be the Arabian plate front) indicates the tectonically active system of the Arabia-Eurasia collision zone, high likely, in the form of lithospheric mantle deformation.

Applying machine learning to characterize and extrapolate the relationship between seismic structure and surface heat flow

SUMMARY Geothermal heat flow beneath the Greenland and Antarctic ice sheets is an important boundary condition for ice sheet dynamics, but is rarely measured directly and therefore is inferred indirectly from proxies (e.g. seismic structure, magnetic Curie depth, surface topography). We seek to improve the understanding of the relationship between heat flow and one such proxy—seismic structure—and determine how well heat flow data can be predicted from the structure (the characterization problem). We also seek to quantify the extent to which this relationship can be extrapolated from one continent to another (the transportability problem). To address these problems, we use direct heat flow observations and new seismic structural information in the contiguous United States and Europe, and construct three Machine Learning models of the relationship with different levels of complexity (Linear Regression, Decision Tree and Random Forest). We compare these models in terms of their interpretability, the predicted heat flow accuracy within a continent and the accuracy of the extrapolation between Europe and the United States. The Random Forest and Decision Tree models are the most accurate within a continent, while the Linear Regression and Decision Tree models are the most accurate upon extrapolation between continents. The Decision Tree model uniquely illuminates the regional variations of the relationship between heat flow and seismic structure. From the Decision Tree model, uppermost mantle shear wave speed, crustal shear wave speed and Moho depth together explain more than half of the observed heat flow variations in both the United States [$r^2 \approx 0.6$ (coefficient of determination), $\mathrm{RMSE} \approx 8\, {\rm mW}\,{\rm m}^{-2}$ (Root Mean Squared Error)] and Europe ($r^2 \approx 0.5, \mathrm{RMSE} \approx 13\, {\rm mW}\,{\rm m}^{-2}$), such that uppermost mantle shear wave speed is the most important. Extrapolating the U.S.-trained models to Europe reasonably predicts the geographical distribution of heat flow [$\rho = 0.48$ (correlation coefficient)], but not the absolute amplitude of the variations ($r^2 = 0.17$), similarly from Europe to the United States ($\rho = 0.66, r^2 = 0.24$). The deterioration of accuracy upon extrapolation is caused by differences between the continents in how seismic structure is imaged, the heat flow data and intrinsic crustal radiogenic heat production. Our methods have the potential to improve the reliability and resolution of heat flow inferences across Antarctica and the validation and cross-validation procedures we present can be applied to heat flow proxies other than seismic structure, which may help resolve inconsistencies between existing subglacial heat flow values inferred using different proxies.

Impact of eliminating ungated access regions on DC and thermal performance of GaN-based MIS-HEMT

The impacts of eliminating access regions (AR) on DC and thermal performance of GaN-based MIS-HEMT have been studied using a device of 4 µm gate length. Nominal absence of ARs was achieved by a metal-organic chemical vapor deposition-regrown heavily n-doped GaN contact region extended to the two-dimensional electron gas (2DEG) channel (with sheet resistance as low as 14 Ω/ ◻ and ohmic contact resistance of 0.20 Ω⋅ mm) and 22-nm-thick AlN/Al2O3/HfO2 insulator layers acting as both gate dielectrics and sidewall spacers. As a result, a low knee voltage (2.5 V @ VGS = +2 V) comparable to deeply-scaled devices was attained, revealing the dominant role of ARs in knee voltages. High linearity at lower supply voltages (gate voltage swing of 7.3 V @ VDS = 5 V) and a faster GVS saturation trend with V DS increasing were observed, benefiting from the improved utility of applied lateral voltage. Moreover, a much lower thermal resistance compared to that of the conventional MIS-HEMT structure (146 vs. 202 K W−1) was extracted by a static-pulsed I-V measurement method. Simplified TCAD simulations were conducted to explain the underlying mechanisms, demonstrating that the enhanced surface heat flow covered by the gate metal as well as the more uniform electric field along the 2DEG channel accounts for the better capability of heat management in the device free of ARs. Our results indicate the size of DC and thermal performance enhancements obtained by eliminating ARs in a GaN-based MIS-HEMT structure.

The contradiction between lithospheric thermal and seismic structures reveals a nonsteady thermal state – A case study from Northeast China

The nature of the lithosphere, as the outermost layer of the solid Earth, has long been a focus of the Earth sciences. Many methods have been used to study the properties and structure of the lithosphere, including gravity, magnetism, electricity, seismic, and geothermics. Since the 1970 s, a coupled heat-flow heat-production steady-state model has been employed to study the thermal structure of the continental lithosphere and has helped researchers explain many geothermal observations. However, the steady-state model does not work well in some areas. Taking Northeast China as a case study, we systematically calculated the lithospheric thermal structure, compared the result with seismic research, and concluded that the lithospheric thermal state is nonsteady in the southern Songliao Basin, the southern Greater Xing’an Range and the Changbai Volcano. The lithosphere in southern Songliao Basin features a hot top and a cold bottom. The lithosphere in southern Greater Xing’an Range and the Changbai Volcano feature a cold top and a hot bottom. Our numerical simulation has demonstrated that the response of surface heat flow to thermal disturbance at the bottom of the lithosphere often lags by more than 20 Myr, resulting in a significant disparity between the thermal structure calculated based on surface heat flow and the velocity structure of seismic waves. In addition, this study of the thermal structure in Northeast China shows that the temperature of the Moho in Songliao Basin is very high (>600 °C), which may be an important cause of the lack of Cenozoic volcanism in the Songliao Basin.

REHEATFUNQ (REgional HEAT-Flow Uncertainty and aNomaly Quantification) 2.0.1: a model for regional aggregate heat flow distributions and anomaly quantification

Abstract. Surface heat flow is a geophysical variable that is affected by a complex combination of various heat generation and transport processes. The processes act on different lengths scales, from tens of meters to hundreds of kilometers. In general, it is not possible to resolve all processes due to a lack of data or modeling resources, and hence the heat flow data within a region is subject to residual fluctuations. We introduce the REgional HEAT-Flow Uncertainty and aNomaly Quantification (REHEATFUNQ) model, version 2.0.1. At its core, REHEATFUNQ uses a stochastic model for heat flow within a region, considering the aggregate heat flow to be generated by a gamma-distributed random variable. Based on this assumption, REHEATFUNQ uses Bayesian inference to (i) quantify the regional aggregate heat flow distribution (RAHFD) and (ii) estimate the strength of a given heat flow anomaly, for instance as generated by a tectonically active fault. The inference uses a prior distribution conjugate to the gamma distribution for the RAHFDs, and we compute parameters for a uninformed prior distribution from the global heat flow database by Lucazeau (2019). Through the Bayesian inference, our model is the first of its kind to consistently account for the variability in regional heat flow in the inference of spatial signals in heat flow data. Interpretation of these spatial signals and in particular their interpretation in terms of fault characteristics (particularly fault strength) form a long-standing debate within the geophysical community. We describe the components of REHEATFUNQ and perform a series of goodness-of-fit tests and synthetic resilience analyses of the model. While our analysis reveals to some degree a misfit of our idealized empirical model with real-world heat flow, it simultaneously confirms the robustness of REHEATFUNQ to these model simplifications. We conclude with an application of REHEATFUNQ to the San Andreas fault in California. Our analysis finds heat flow data in the Mojave section to be sufficient for an analysis and concludes that stochastic variability can allow for a surprisingly large fault-generated heat flow anomaly to be compatible with the data. This indicates that heat flow alone may not be a suitable quantity to address fault strength of the San Andreas fault.

Antarctic Geothermal Heat Flow, Crustal Conductivity and Heat Production Inferred From Seismological Data

AbstractGeothermal heat flow is a key parameter in governing ice dynamics, via its influence on basal melt and sliding, englacial rheology, and erosion. It is expected to exhibit significant lateral variability across Antarctica. Despite this, surface heat flow derived from Earth's interior remains one of the most poorly constrained parameters controlling ice sheet evolution. To obtain a continent‐wide map of Antarctic heat supply at regional‐scale resolution, we estimate upper mantle thermomechanical structure directly from VS. Until now, direct inferences of Antarctic heat supply have assumed constant crustal composition. Here, we explore a range of crustal conductivity and radiogenic heat production values by fitting thermodynamically self‐consistent geotherms to their seismically inferred counterparts. Independent estimates of crustal conductivity derived from VP are integrated to break an observed trade‐off between crustal parameters, allowing us to infer Antarctic geothermal heat flow and its associated uncertainty.

Bone density estimation using tissue heat capacity.

Osteoporosis onset is relatively asymptomatic, the condition often being identified only once a significant fracture occurs, leading to a potentially serious prognosis. Currently, early identification of osteoporosis is complicated by the difficulty in measuring bone density without using x-ray absorptiometry or quantitative ultrasound, so a simpler method for estimating bone density is needed. Given that bone is reported to have a lower specific heat than other tissues, we investigated the possibility of estimating bone density using this difference in tissue thermal properties. The tibia medial surface (shin) and medial malleolus (ankle) of 68 healthy volunteers were cooled using an ice bag, and skin surface temperatures and heat flow were recorded. These measurements were then used to calculate the heat energy transferred per unit temperature. Bone density was estimated by quantitative ultrasound using the T score OSISD, which is the participant's osteo sono-assessment index (OSI) compared to the average OSI of young adults. The heat energy transfer per unit temperature at the shin, but not the ankle, showed a significant negative correlation with T score OSISD (r = -0.413, p = 0.001). Multiple regression analysis showed that heat energy transfer per unit temperature at the shin was a significant predictor of T score OSISD, along with age and height. These results show that tissue thermal property measurements are useful for estimating bone density.

A Continental Model of Curie Point Depth for China and Surroundings Based on Equivalent Source Method

AbstractThe Curie Point Depth (CPD) marks a significant temperature boundary (∼580°C) within the Earth's lithosphere. However, there has been ongoing debate regarding its spatial distribution. In this research, we utilized the Equivalent Source Method (ESM) based on Gauss‐Legendre integration and data obtained from the EMM2017 model, along with a five‐layer susceptibility model, to generate a 0.5° × 0.5° grid of continental CPD distribution for China and surroundings. The average CPD in the study area is 30.4 km, which is slightly shallower than the average depth of global continental Moho (∼33 km). Notably, stable and cold cratonic basins, such as the Tarim Basin and the Sichuan Basin, exhibit deep CPD of ∼45 km. In contrast, the North China Craton, which has experienced significant tectono‐thermal activity since the Late Mesozoic, shows moderate CPD of ∼30 km and a gradual uplift from west to east. The Tuva‐Mongol orocline within the Central Asian Orogenic Belt, the Deccan Volcanic Province in the Indian subcontinent and the Eastern Yangtze Craton have shallow CPD of ∼20 km. We estimate the surface heat flow by CPD, and the result is consistent with measurements within a RMSE of 18.1 mW/m2. When comparing the CPD with Moho, we find that the CPD may lie below Moho in stable and cold cratonic areas. In comparison to two recent global CPD models, our regional model demonstrates better alignment with tectonic features.

Blind magmatism abets nonvolcanic continental rifting

Tectonic forces alone cannot drive rifting in old and thick continental lithosphere. Geodynamic models suggest that thermal weakening is critical for lithospheric extension, yet many active rifts lack volcanism, seeming to preclude this process. We focus on one such rift, the Tanganyika-Rukwa segment of the East African Rift System, where we analyze local seismicity for shear wave anisotropy and couple the results with numerical modeling. The strongest splitting measurements are from earthquakes with paths sampling lower crustal regions of high compressional-to-shear wave velocity ratios and have fast polarization directions parallel to the local mantle flow, implying the existence of oriented melt lenses. This lower crustal magmatism and observed high surface heat flow are consistent with substantial lithospheric weakening and explain the enigmatic relief and increasing strain accommodation along the rift axis. We conclude that progressive nonvolcanic rifting is assisted by deep crustal melts yet to breach the surface.