Local Hot Spots Research Articles

Future climatically suitable areas for bats in South Asia.

Climate change majorly impacts biodiversity in diverse regions across the world, including South Asia, a megadiverse area with heterogeneous climatic and vegetation regions. However, climate impacts on bats in this region are not well-studied, and it is unclear whether climate effects will follow patterns predicted in other regions. We address this by assessing projected near-future changes in climatically suitable areas for 110 bat species from South Asia. We used ensemble ecological niche modelling with four algorithms (random forests, artificial neural networks, multivariate adaptive regression splines and maximum entropy) to define climatically suitable areas under current conditions (1970-2000). We then extrapolated near future (2041-2060) suitable areas under four projected scenarios (combining two global climate models and two shared socioeconomic pathways, SSP2: middle-of-the-road and SSP5: fossil-fuelled development). Projected future changes in suitable areas varied across species, with most species predicted to retain most of the current area or lose small amounts. When shifts occurred due to projected climate change, new areas were generally northward of current suitable areas. Suitability hotspots, defined as regions suitable for >30% of species, were generally predicted to become smaller and more fragmented. Overall, climate change in the near future may not lead to dramatic shifts in the distribution of bat species in South Asia, but local hotspots of biodiversity may be lost. Our results offer insight into climate change effects in less studied areas and can inform conservation planning, motivating reappraisals of conservation priorities and strategies for bats in South Asia.

Drone-based monitoring of intertidal blue mussel beds in the Wadden Sea – comparison of a threshold and two machine learning approaches

In the Wadden Sea, intertidal mussel beds of the blue mussel (Mytilus edulis) and the Pacific oyster (Magallana gigas) form distinct epibenthic communities and local hotspots of high biomass and biodiversity. To detect and evaluate natural and anthropogenic processes, a ground-based monitoring program started over 25 years ago in the German Wadden Sea. In this study, we describe the potential of drones and machine learning approaches for a remote sensing-based integration into an existing monitoring program of intertidal mussel beds. A fixed wing drone was used to cover an area of up to 39ha in a single flight, with an overall time saving potential of 50%. Applying machine learning approaches, a detailed extraction of the intertidal blue mussel bed coverage with an overall accuracy (OA) up to 95.6% was reached, applying a Support Vector Machine (SVM). The application of a multispectral sensor improved the classification performance. Compared to ground-based monitoring, the drone-based method provided significantly more information on the area extension, coverage, and associated algae of the mussel beds. The results show that drones can provide a non-invasive way to survey large and difficult to access areas providing detailed maps of mussel beds and their internal structures.

Effectiveness of Using AI-Driven Hotspot Mapping for Active Case Finding of Tuberculosis in Southwestern Nigeria.

Background: Nigeria is among the top five countries that have the highest gap between people reported as diagnosed and estimated to have developed tuberculosis (TB). To bridge this gap, there is a need for innovative approaches to identify geographical areas at high risk of TB transmission and targeted active case finding (ACF) interventions. Leveraging community-level data together with granular sociodemographic contextual information can unmask local hotspots that could be otherwise missed. This work evaluated whether this approach helps to reach communities with higher numbers of undiagnosed TB. Methodology: A retrospective analysis of the data generated from an ACF intervention program in four southwestern states in Nigeria was conducted. Wards (the smallest administrative level in Nigeria) were further subdivided into smaller population clusters. ACF sites and their respective TB screening outputs were mapped to these population clusters. This data were then combined with open-source high-resolution contextual data to train a Bayesian inference model. The model predicted TB positivity rates on the community level (population cluster level), and these were visualised on a customised geoportal for use by the local teams to identify communities at high risk of TB transmission and plan ACF interventions. The TB positivity yield (proportion) observed at model-predicted hotspots was compared with the yield obtained at other sites identified based on aggregated notification data. Results: The yield in population clusters that were predicted to have high TB positivity rates by the model was at least 1.75 times higher (p-value < 0.001) than the yield in other locations in all four states. Conclusions: The community-level Bayesian predictive model has the potential to guide ACF implementers to high-TB-positivity areas for finding undiagnosed TB in the communities, thus improving the efficiency of interventions.

New data and taxonomic changes influence our understanding of biogeographic patterns: A case study in Australian skinks

AbstractSpecies are the most commonly used unit of biogeography research, and in many conservation schemes. For many faunal groups, taxonomy is in a constant state of flux, with new species being described, and our concept of existing species regularly being refined. Using the most diverse lineage of Australian lizards (460+ species), the skinks (Family Scincidae), we quantified the impacts of taxonomic changes over time on our understanding of species richness, endemism and beta diversity. We generated surfaces of species richness, endemism and beta diversity from four editions (1975, 1988, 2000, 2014) of an authoritative field guide to understand how taxonomic shifts, and enhanced biogeographic knowledge, influenced the inferred biogeographic patterns in Australian skinks. The number of recognized Australian skink species has increased 2.3‐fold since 1975. The Wet Tropics was the major hotspot for (mostly locally endemic) species additions. Hotspots of species richness and beta diversity remained broadly similar over time, but some important local hotspots shifted. Endemism hotspots were weakly associated with hotspots of species additions over time except in the Wet Tropics. The major shifts in biogeographic patterns, which were not associated with taxonomic changes, resulted from better knowledge of species distributions through time. We hypothesize that the effects of taxonomy on biogeographic patterns we found generalize across clades and regions—especially away from major research hotspots. We suggest an understanding of the impact of taxonomic changes on conservation priorities for particular regions and taxonomic groups is needed.

Criterion for void nucleation by particle debonding in metals obtained from molecular dynamics simulations

The critical conditions for void nucleation by particle debonding at a θ-particle in an aluminum matrix are identified through a comprehensive set of molecular dynamics simulations spanning a range of stress triaxialities and Lode parameter values. Specifically, it is determined that nucleation occurs when the local normal stress at the matrix–particle interface reaches a critical value of 8.14 GPa. When plasticity occurs in the matrix prior to nucleation, an additional plastic stress concentration is observed as a result of the plastic strain build up around the particle. Our results indicate that this plastic stress concentration factor increases roughly linearly with equivalent plastic strain, independent of triaxiality and Lode parameter. Comparing our results with the literature, we observe a much stronger influence of plastic strain than is predicted by continuum plasticity theory. We argue that this difference derives from the fact that nucleation is fundamentally driven by local stress hot spots resulting from the heterogeneity of plastic strain, while continuum theory is based on homogenized plastic strain fields. These results provide guidance for development of ductile fracture engineering models, while giving a warning regarding the use of continuum theory to predict damage initiation phenomena in metals.

Zoogeochemistry of a protected area: Driven by anthropogenic impacts and animal behavior

AbstractAnthropogenic eutrophication of ecosystems is an important driver of biodiversity loss. Even protected areas (PAs) may be impacted by anthropogenic nutrients, for example, from atmospheric deposition or the provision of supplementary feeding. However, the resultant nutrient patterns, and the role of local wildlife in shaping them, remain poorly understood. We investigated anthropogenic influences on the role that red deer (Cervus elaphus) play in the nutrient balance of a PA in Denmark. We used habitat selection modeling and theoretical scenarios where we varied the proportion of energy the deer obtained from supplementary versus natural forage and compared it with the nutrients removed due to hunting. We show that the movement and distribution of the red deer population within the PA are very heterogeneous and likely influenced by the need for shelter. Moreover, depending on their reliance on supplementary feeding, deer can potentially import large amounts of nutrients to the PA, and concentrate them in localized hotspots. However, we also explore the potential for nutrient loss due to hunting activities. Such indirect anthropogenic impacts on nutrient landscapes may counteract restoration and conservation efforts. We therefore recommend incorporating anthropogenic influences on zoogeochemistry and the animal‐mediated connectivity between PAs and anthropogenically dominated landscapes into future management plans.

Thermally stable Ni foam-supported inverse CeAlOx/Ni ensemble as an active structured catalyst for CO2 hydrogenation to methane

Nickel is the most widely used inexpensive active metal center of the heterogeneous catalysts for CO2 hydrogenation to methane. However, Ni-based catalysts suffer from severe deactivation in CO2 methanation reaction due to the irreversible sintering and coke deposition caused by the inevitable localized hotspots generated during the vigorously exothermic reaction. Herein, we demonstrate the inverse CeAlOx/Ni composite constructed on the Ni-foam structure support realizes remarkable CO2 methanation catalytic activity and stability in a wide operation temperature range from 240 to 600 °C. Significantly, CeAlOx/Ni/Ni-foam catalyst maintains its initial activity after seven drastic heating-cooling cycles from RT to 240 to 600 °C. Meanwhile, the structure catalyst also shows water resistance and long-term stability under reaction condition. The promising thermal stability and water-resistance of CeAlOx/Ni/Ni-foam originate from the excellent heat and mass transport efficiency which eliminates local hotspots and the formation of Ni-foam stabilized CeAlOx/Ni inverse composites which effectively anchored the active species and prevents carbon deposition from CH4 decomposition.

Experimental investigation of nonuniform PV soiling

Photovoltaic (PV) module soiling, i.e., the accumulation of dust on PV module surfaces, poses several challenges to PV system performance. Among these challenges, the nonuniform deposition of soiling across the module surface has received scarce attention. Soiling is directly associated with an overall performance loss, but can also potentially give rise to localised hotspots that can lead to long-term PV module failure. Therefore, addressing the issues arising from this nonuniformity is not only important for optimising energy production, but also for enhancing system reliability, and ensuring the long-term operation of relevant power generation systems. In this study, the impact of nonuniform soiling on PV performance is investigated experimentally by examining soil deposition on the upper surfaces of low-iron glass samples. Samples positioned at four different tilt angles were collected on a monthly basis over a one-year study period. Since the horizontal samples were found to represent the worst-case conditions, the most soiled sample at horizontal tilt was divided into four zones, each housing a single monocrystalline solar cell and examined further. The findings reveal that the soiled sample experiences an average transmittance deterioration of 13% relative to a clean sample, and a maximum (relative) spatial variation of 4% between the four zones. These optical losses affect the amount of sunlight received by the cells, resulting in a power deterioration of ∼6–7% per 5% drop in transmittance. The soiled sample experienced an average temperature rise of 2 °C, and an average power output (and efficiency) reduction of 30% relative to the clean sample, and a maximum (relative) spatial variation of 7% between the zones. The 30% average power loss measured in this nonuniform soiling case is more than double that which would be expected theoretically for a transmittance loss of 13% but from uniform soiling, so these results highlight the importance of addressing PV soiling for optimal PV performance, and of accounting for spatial soiling nonuniformity.

A Metamaterial-like Structure Design Using Non-uniformly Distributed Dielectric and Conducting Strips to Boost the RF Field Distribution in 7 T MRI.

Metamaterial-based designs in ultra-high field (≥7 T) MRI have the promise of increasing the local magnetic resonance imaging (MRI) signal and potentially even the global efficiency of both the radiofrequency (RF) transmit and receive resonators. A recently proposed metamaterial-like structure-comprised of a high-permittivity dielectric material and a set of evenly distributed copper strips-indeed resulted in a local increase in RF transmission. Here, we demonstrate that non-uniform designs of this metamaterial-like structure can be used to boost the ultimate RF field distribution. A non-uniform dielectric distribution can yield longer electric dipoles, thus extending the RF transmit field coverage. A non-uniform distribution of conducting strips enables the tailoring of the local electric field hot spots, where a concave distribution resulted in lower power deposition. Simulations of the brain and calf regions using our new metamaterial-like design, which combines non-uniform distributions of both the dielectric and conducting strips, revealed a 1.4-fold increase in the RF field coverage compared to the uniform distribution, and a 1.5-2-fold increase in the transmit efficiency compared to the standard surface-coil.

Dynamic and stationary monitoring of air pollutant exposures and dose during marathons

Marathon running significantly increases breathing volumes and, consequently, air pollution inhalation doses. This is of special concern for elite athletes who ventilate at very high rates. However, race organizers and sport governing bodies have little guidance to support events scheduling to protect runners. A key limitation is the lack of hyper-local, high temporal resolution air quality data representative of exposure along the racecourse. This work aimed to understand the air pollution exposures and dose inhaled by athletes, by means of a dynamic monitoring methodology designed for road races. Air quality monitors were deployed during three marathons, monitoring nitrogen dioxide (NO2), ozone (O3), particulate matter (PMx), air temperature, and relative humidity. One fixed monitor was installed at the Start/Finish line and one mobile monitor followed the women elite runner pack. The data from the fixed monitors, deployed prior the race, described daily air pollution trends. Mobile monitors in combination with heatmap analysis facilitated the hyper-local characterization of athletes' exposures and helped identify local hotspots (e.g., areas prone to PM resuspension) which should be preferably bypassed. The estimation of inhaled doses disaggregated by gender and ventilation showed that doses inhaled by last finishers may be equal or higher than those inhaled by first finishers for O3 and PMx, due to longer exposures as well as the increase of these pollutants over time (e.g., 58.2 ± 9.6 and 72.1 ± 23.7 μg of PM2.5 for first and last man during Rome marathon). Similarly, men received significantly higher doses than women due to their higher ventilation rate, with differences of 31–114 μg for NO2, 79–232 μg for O3, and 6–41 μg for PMx. Finally, the aggregated data obtained during the 4 week- period prior the marathon can support better race scheduling by the organizers and provide actionable information to mitigate air pollution impacts on athletes' health and performance.

Warunki koegzystencji ludzi z infrastrukturą elektromagnetycznych technologii radiokomunikacyjnych w wybranych mikrośrodowiskach

This is a study of how people coexisting with the infrastructure of electromagnetic mobile communication technologies emitting radio waves in the work and living environment: (i) in passenger trains, (ii) in shopping centres and (iii) in passenger cars. It revealed significantly different trends, over the last five years (2018-2023), in the structure of exposure to radio waves, with slight changes in the level of total exposure in analysed environments used by workers and the public. The observed changes are related to the spread of mobile access to fast data transfer and increased speed of transmission from personal devices (terminals such as smartphones or tablets). The results from shopping centres showed dominant downlink-components of exposure (from base stations) and a broadening of their frequency band (due to the spread of LTE subscription services using the 2100 and 2600 MHz bands) in 2023, along with reduced uplink-components (from terminals) and components related to local hotspots of non-subscription networks (Wi-Fi). A broadening of the frequency band was also observed in measurements from passenger trains, but with the dominant uplink-components of exposure, regardless of the availability of local hotspots. In passenger cars, exposure to external radio waves (downlink components) also broadened in the frequency band (in the LTE 800 and 2600 MHz bands). A reduction in exposure fluctuations over time was found in all the studied microenvironments. This implies that different measures are necessary to reduce workers’ exposure, along with different methods of identifying and assessing the parameters there.

Satellite-Derived Estimate of City-Level Methane Emissions from Calgary, Alberta, Canada

Cities are important sources of anthropogenic methane emissions. Municipal governments can play a role in reducing those emissions to support climate change mitigation, but they need information on the emission rate to contextualize mitigation actions and track progress. Herein, we examine the application of satellite data from the TROPOspheric Monitoring Instrument (TROPOMI) to estimate city-level methane emission rates in a case study of the City of Calgary, Alberta, Canada. Due to low and variable annual observational coverage, we integrated valid TROPOMI observations over three years (2020–2022) and used mass balance modeling to derive a long-term mean estimate of the emission rate. The resulting column-mean dry-air mole fraction (XCH4) enhancement over Calgary was small (4.7 ppb), but within the city boundaries, we identified local hot spots in the vicinity of known emission sources (wastewater treatment facilities and landfills). The city-level emission estimate from mass balance was 215.4 ± 132.8 t CH4/d. This estimate is approximately four times larger than estimates from Canada’s gridded National Inventory Report of anthropogenic CH4 emissions and six times larger than the Emissions Database for Global Atmospheric Research (EDGAR v8.0). We note that valid TROPOMI observations are more common in warmer months and occur during a narrow daily overpass time slot over Calgary. The limited valid observations in combination with the constrained temporal observational coverage may bias the emission estimate. Overall, the findings from this case study highlight an approach to derive a screening-level estimate of city-level methane emission rates using TROPOMI data in settings with low observational coverage.

Numerical investigation of air flow characteristics for a compact 5 [formula omitted] 10 array tubular segmented-in-series solid oxide fuel cell stack

Tubular segmented-in-series solid oxide fuel cells (SIS-SOFCs) offer the advantages of high voltage, low current, easy sealing, and high thermal shock resistance. Tubular SIS-SOFCs can be assembled into a highly integrated power-generation stack module to increase the volumetric power density. This study investigated the air flow characteristics of a kilowatt-class tubular SIS-SOFC stack with a 5 × 10-cell array, each containing 59 segments. A three-dimensional stack model that considers practical stack structures, coupled electrochemical reactions, and the mass/momentum/heat transfer processes was developed. The results show that a large flow nonuniformity existed in the conventional tubular stack design, which resulted in a severe temperature distribution. Local hot spots at the marginal positions and circumferential temperature difference were found to be non-negligible. To improve the flow uniformity, an air distributor with optimized diameters at different positions was designed, and manifold parameters were adjusted to balance the flow resistance. The maximum temperature was reduced by 35 K and temperature uniformity was significantly improved.

Elevation modulates the impacts of climate change on the Brazilian Cerrado flora

AbstractAimClimate change is causing species distribution to shift across the globe. Lowland taxa are moving upslope with warming, while montane species face extinction. We tested the hypothesis that elevation controls the future distribution of plant species in the Brazilian Cerrado, home of 3.5% of the Earth's flowering plants (c. 5000 endemic species) in just 0.4% of the planet's land surface.LocationCerrado region in Brazil.MethodsWe estimated geographical range shifts of 7398 angiosperm species by 2040 using species distribution models (SDMs). We stacked the SDMs to derive the temporal variations of species richness and composition over the Cerrado.ResultsOur results show that between 50 and 52% of the Cerrado flora will experience net range loss due to climate change. While montane species were more likely to lose range, range gain was more common among lowland taxa. We estimate that 68–73% of the Cerrado extent will face net species losses by 2040. Net species loss was more likely to occur below 743–798 metres above sea level. Virtually the entire Cerrado will experience some level of species replacement due to climate change and species turnover will intensify as elevation increases.Main ConclusionsOur findings suggest that upslope migration allows lowland plants to track climate change (‘winners’), whereas montane taxa do not (‘losers’). As species move upslope, lowlands become local extinction hotspots and mountains harbour novel plant assemblages. Therefore, elevation exerts a central role in shaping Cerrado flora responses to climate change and potentially the long‐term efficacy of conservation and restoration efforts.

The effect of silica nanoparticles on the shock adiabatic relation and tensile strength in polyurethane

This work exploded the effect of silica nanoparticles on shock adiabatic relation and tensile fracture in polyurethane based on atomistic simulations. It is found that the non-uniform interface structures introduced by nanoparticles can increase the shock impedance, which also leading to increased twisting of polyurethane chains and the generation of local hotspots near the nanoparticles. The interface structures near the nanoparticle consists of polyurethane chains with a high gyration radius, and the average gyration radius increases approximately linearly with the increase in nanoparticle content. At lower shock velocity, the potential energy increment initially increases and then decreases with the increase in nanoparticle content. Bond analysis reveal that flexible segments dominate the bending and twisting deformations of polyurethane, while nanoparticles enhance the corresponding deformation degrees. Furthermore, nanoparticles can serve as void nucleation sites for early-stage tensile damage, resulting in a decrease in fracture strength. Differing from metals, the relationship between tensile strength and fracture temperature follows a more linear law. Nanoparticles inhibit the later growth and coalescence of voids by increasing the temperature and steric hindrance. The density and size distribution characteristics of voids are consistent with the changes in potential energy during the shock compression process. Unlike classical spallation, the curled polyurethane chains in the tensile region gradually orient along the shock direction, evolving into a void-fiber structure.

Abstract 1206: Three-dimensional immune atlas of pancreatic cancer precursor lesions reveals large inter- and intra-lesion heterogeneity

Abstract Immunotherapies are generally ineffective in pancreatic ductal adenocarcinoma (PDAC). Paradoxically, inflammation is believed to play a key role in PDAC development and invasion: patients suffering from chronic pancreatitis have a 13-fold increase in risk of developing PDAC. PDAC cells are surrounded by a dense network of fibrotic tissue containing immunosuppressive cells such as regulatory T cells, tumor-associated macrophages, and cancer-associated fibroblasts. Better understanding of the role of inflammation in PDAC could lead to the design of effective immunotherapies. Pancreatic intraepithelial neoplasia (PanIN) is a precursor to PDAC. While most of us will develop PanINs, few of these lesions will progress to invasive cancer. Efforts to determine which PanINs are likely to progress have shown that the size, incidence, and genetic variation of these lesions is high. Here, we add to these efforts through in-depth quantitative analysis of the pancreatic immune microenvironment. CODA is a novel 3D imaging technique used extensively to study the structure, transcriptomic signatures, and genetic heterogeneity of PanINs. In serial histological samples, CODA integrates image registration, cell detection, and segmentation of nine pancreatic structures: PanIN, normal ducts, islets, acini, nerves, vasculature, fat, stroma, and immune aggregates. Through integration with CD45, CD3, and FoxP3 labelled images, we explored immune infiltration in 48 large (cm3) samples of human pancreas tissues containing &amp;gt;1,000 PanIN lesions to describe spatial correlations between local immune hotspots, 3D tumor morphology, and the surrounding pancreas structures. We quantified inter- and intra-sample heterogeneity in immune response to pancreatic cancer precursor lesions. We determined that this cohort varied greatly in both the number of PanIN (range 3 - 92 per cm3) and overall immune cell density (range 3,000 - 40,000 immune cells/mm3). We determined that, while PanIN size is not related to local immune cell density, overall PanIN burden is highly correlated to global immune cell density. This suggests that PanIN content does not have a short-range relationship to inflammation, but does have a long-range relationship with pancreatic structures and immune infiltration. As chronic inflammation in the pancreas shows correlation with development of pancreatic cancer, increased knowledge of the heterogeneous, local immune cell environment in precancerous samples will help us determine the role of inflammation in reacting to and controlling malignant progression. Citation Format: Ashley L. Kiemen, Cristina Almagro-Pérez, Valentina Matos-Romero, Alicia M. Braxton, Jaanvi Mahesh-Babu, Elizabeth D. Thompson, Toby C. Cornish, PeiHsun Wu, Laura D. Wood, Arrate Muñoz-Barrutia, Ralph H. Hruban, Denis Wirtz. Three-dimensional immune atlas of pancreatic cancer precursor lesions reveals large inter- and intra-lesion heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1206.

Laser-induced thermal runaway dynamics of cylindrical lithium-ion battery

Laser is a precise, remote, and non-invasive heating method that can initiate thermal runaway of lithium-ion batteries in safety tests. This study systemically explores the thermal runaway of cylindrical cells induced by constant laser irradiation up to 20 W and 1.6 MW m−2 within a 4-mm diameter spot. Results indicate that thermal runaway intensity is relatively insensitive to the laser power but controlled by the battery state of charge (SOC). The overall heating efficiency of the laser (78 ± 7 %) is higher than that of the oven and comparable to contact heating methods. As the battery SOC decreases from 100 % to 30 %, the minimum laser output power for thermal runaway increases from 9.5 W to 15 W, corresponding to the effective battery heating power rising from 6.7 W to 11.1 W. These critical values hold significance in evaluating the thermal hazards associated with localized hotspot failures. Finally, the strategy for applying the laser to trigger the battery thermal runaway is proposed based on a simplified heat transfer model. This work reveals the battery fire risk under high-intensity spot heating and provides a valuable scientific basis for using laser heating in battery safety test standards.

Numerical investigation of parameter distributions in high-temperature PEMFCs under various cooling surface temperature gradients

Non-uniform current density distribution can lead to localized hotspots, resulting in shortened lifespans of fuel cells. The temperature distributions on the bipolar plate cooling surface significantly influence various parameters within a fuel cell. This study develops a mathematical model for a high-temperature proton exchange membrane fuel cell (HT-PEMFC) to simulate its operation in four different directions of temperature gradient on the cooling surface. The distributions of membrane temperature, proton conductivity, oxygen concentration, activation loss, and current density were obtained to clarify the interaction mechanism between cooling surface temperature and these parameters in fuel cell. The results show that the membrane temperature and proton conductivity increase and the oxygen concentrations decrease with increasing cooling surface temperature. A lower temperature in the catalyst layer regions leads to a decrease in the current density. In particular, when the cooling surface temperature distribution is characterized by a temperature decrease in the upstream area with a high reactant concentration and an increase in the downstream area with a low reactant concentration, the fuel cell has an excellent current density uniformity, which reaches 92.61 % at a voltage of 0.6 V and a cooling surface temperature difference of 10 K.

Insight into the influence of frictional heat on the modal characteristics and interface temperature of frictionally damped turbine blades

The reciprocating relative motions of friction pairs introduce nonlinearities into the host structure, while also generating frictional heat, leading to a noticeable temperature rise at the contact interface. Consequently, the contact mechanics properties are not invariant but highly dependent on temperature. To elucidate the thermo-mechanical interaction mechanism in dry friction systems, we propose a novel multi-physical nonlinear modal analysis method called Thermo-Mechanical damped Nonlinear Normal Mode (TM-dNNM). This numerical method enables the determination of nonlinear modal characteristics considering thermo-mechanical coupling and the prediction of detailed temperature distribution on contact interface. The efficiency and convergence of the TM-dNNM are ensured through three key techniques: multi-physics reduced order modeling, analytical Jacobian matrix, and scaling adjustment. We apply the proposed numerical method to a typical turbine blade with a flat underplatform damper for engineering purposes. Results indicate that frictional heat significantly affects the nonlinear modal characteristics, exhibiting complex behavior such as softening/stiffening reversal and resonance amplitude backtracking. Neglecting the thermo-mechanical coupling can lead to a deviation of more than 13 Hz in the predicted modal frequency and an overestimation of the modal damping ratio by a factor of three. Interface temperature rises considerably at higher vibration levels, with the hotspot located near the lower left corner of the contact surface, where the average temperature exceeds 1180 ℃, approaching the melting point. By employing the TM-dNNM, designers can predict critical resonance amplitudes and identify potential local hotspots, thus helping prevent excessive temperature at the interface of frictionally damped turbine blades.

Multi-objective optimization of temperature uniformity in the immersion liquid cooling cabinet with Taguchi-based grey relational analysis

Single-phase immersion liquid cooling technology can meet the cooling needs of high-density Data Centers. To improve the temperature uniformity in an immersion liquid cooling cabinet and prevent local hot spots that reduce the efficiency of servers, the structural parameters of the cabinet were optimized in this study. The fluid path is mainly affected by the position of inlet and outlet, length, Angle and number of baffles. To evaluate the effects of these factors on the temperature uniformity in the cabinet, Taguchi-based grey relational analysis method and computational fluid dynamics were used to optimize the system, the standard deviation and maximum temperature difference are determined as evaluation indices, and L16 (44) orthogonal array was used for experimental design. The baffle Angle is judged to be the most important structural parameter by the Main Effect Analysis, whose contribution rate is 49.23%. The multi-objective optimization is transformed into a single objective by the grey relational analysis, and the influence rate of each structural parameter is shown. The optimal combination of structural parameters is determined. The results show that the temperature uniformity of the optimized cabinet is improved by 46%, which provides a reference for the design of immersion liquid cooling Data Centers.