Search Results (21)

This paper presents methods and applications of inverse heat conduction problems (IHCPs) that are ill-posed in the Hadamard sense. The IHCP solution allows for the determination of boundary conditions in the form of heat flux or temperature in places where measurement is impossible or difficult to perform. The applications of IHCP solutions to energy-intensive industrial processes, such as heat treatment and thermochemical treatment, are described. Examples are given of determining boundary conditions on the inner surface of the wall of a power boiler and piston machine, as well as on the surface of a gas turbine blade. It is noted that the application of IHCP solutions to the above-mentioned issues often requires simplification of the computational model, in particular, the method of stabilising the inverse problem (IP). For this purpose, quasi-regularisation of IP and machine learning are currently used. Methods with stabilising properties and neural networks were identified as a challenging and interesting direction for the development of IHCP solutions. Full article

In this study, a three-dimensional Inverse Conjugate Heat Transfer Problem (ICHTP) is numerically and experimentally investigated to estimate the heat-source strength of multiple chips mounted on a printed circuit board (PCB) using the Conjugate Gradient Method (CGM) and infrared thermography. The interfaces between the PCB and the surrounding air domain are assumed to exhibit perfect thermal contact, establishing a fully coupled conjugate heat transfer framework for the inverse analysis. Unlike the conventional Inverse Heat Conduction Problem (IHCP), which typically only accounts for conduction within solid domains, the present ICHTP formulation requires the simultaneous solution of the governing continuity, momentum, and energy equations in the air domain, along with the heat conduction equation in the chips and PCB. This coupling introduces substantial computational complexity due to the nonlinear interaction between convective and conductive heat transfer mechanisms, as well as the sensitivity of the inverse solution to measurement uncertainties. The numerical simulations are conducted first with error-free measurement data and an inlet velocity of u_in = 4 m/s; the recovered heat-sources exhibit excellent agreement with the true values. The computed average errors for the estimated temperatures ERR1 and estimated heat sources ERR2 are as low as 0.0031% and 1.87%, respectively. The accuracy of the estimated heat sources is then experimentally validated under various prescribed inlet air velocities. During experimental verification at an inlet velocity of 4 m/s, the corresponding ERR1 and ERR2 values are obtained as 0.91% and 3.34%, while at 6 m/s, the values are 0.86% and 2.81%, respectively. Compared with the numerical results, the accuracy of the experimental estimations decreases noticeably. This discrepancy arises because the numerical simulations are free from measurement noise, whereas experimental data inherently include uncertainties due to thermal picture resolutions, environmental fluctuations, and other uncontrollable factors. These results highlight the inherent challenges associated with inverse problems and underscore the critical importance of obtaining precise and reliable temperature measurements to ensure accurate heat source estimation. Full article

This study presents a quantum electrodynamics (QED) framework that explains the anomalous behavior of liquid water. The theory posits that water consists of two coexisting phases: a coherent phase, in which molecules form phase-locked coherence domains (CDs), and an incoherent phase that behaves like a dense van der Waals fluid. By solving polynomial-type equations, we derive key thermodynamic properties, including the minima in the isobaric heat capacity per particle (IHCP) and the isothermal compressibility, as well as the divergent behavior observed near 228 K. The theory also accounts for water’s high static dielectric constant. These results emerge from first-principles QED, integrating quantum coherence with macroscopic thermodynamics. The framework offers a unified explanation for water’s anomalies and has implications for biological systems, materials science, and fundamental physics. Future work will extend the theory to include phase transitions, solute interactions, and the freezing process. Full article

High-voltage ceramic insulators are routinely exposed to short-duration overvoltages such as lightning impulses, switching surges, and partial discharges. These events occur on microsecond to millisecond timescales and can produce highly localized thermal spikes that are difficult to measure directly but may compromise long-term material integrity. This paper addresses the estimation of the internal temperature distribution immediately after a lightning impulse by solving a three-dimensional inverse heat conduction problem (IHCP). The forward problem is modeled by the transient heat diffusion equation with constant thermal diffusivity, discretized using the finite element method (FEM). Surface temperature measurements are assumed available from a 12 kV ceramic post insulator and are used to reconstruct the unknown initial condition. To address the ill-posedness of the IHCP, a spatio-temporal regularization framework is introduced and compared against spatial-only regularization. Numerical experiments investigate the effect of measurement time ($T=60$ s, 600 s, and 1800 s), mesh resolution (element sizes of 20 mm, 15 mm, and 10 mm), and measurement noise ($\sigma =1$ K and 5 K). The results show that spatio-temporal regularization significantly improves reconstruction accuracy and robustness to noise, particularly when early-time measurements are available. Moreover, it is observed that mesh refinement enhances accuracy but yields diminishing returns when measurements are delayed. These findings demonstrate the potential of spatio-temporal IHCP methods as a diagnostic tool for the condition monitoring of ceramic insulators subjected to transient electrical stresses. Full article

In high-temperature testing scenarios that rely on contact, fine-wire thermocouples demonstrate commendable dynamic performance. Nonetheless, their thermal inertia leads to notable dynamic nonlinear inaccuracies, including response delays and amplitude reduction. To mitigate these challenges, a novel dynamic error correction approach is introduced, which combines a Continuous Restricted Boltzmann Machine, Deep Belief Network, and Physics-Informed Neural Network (CDBN-PINN). The unique heat transfer properties of the thermocouple’s bimetallic structure are represented through an Inverse Heat Conduction Equation (IHCP). An analysis is conducted to explore the connection between the analytical solution’s ill-posed nature and the thermocouple’s dynamic errors. The transient temperature response’s nonlinear characteristics are captured using CRBM-DBN. To maintain physical validity and minimize noise amplification, filtered kernel regularization is applied as a constraint within the PINN framework. This approach was tested and confirmed through laser pulse calibration on thermocouples with butt-welded and ball-welded configurations of 0.25 mm and 0.38 mm. Findings reveal that the proposed method achieved a peak relative error of merely 0.83%, superior to Tikhonov regularization by −2.2%, Wiener deconvolution by 20.40%, FBPINNs by 1.40%, and the ablation technique by 2.05%. In detonation tests, the corrected temperature peak reached 1045.7 °C, with the relative error decreasing from 77.7% to 5.1%. Additionally, this method improves response times, with the rise time in laser calibration enhanced by up to 31 ms and in explosion testing by 26 ms. By merging physical constraints with data-driven methodologies, this technique successfully corrected dynamic errors even with limited sample sizes. Full article

Background: Organoid cultures have received much attention in recent years due to the promise of patient-derived organoid cultures for exploration of personalized cancer treatment strategies. Organoid cultures have been established from a variety of malignancies; however, lack of a thorough histopathological analysis has limited the acceptance of organoid models as translational tools. Methods: Here, we aimed to establish patient-derived tumor-organoid (PDTO) models from human non-small-cell lung cancer (NSCLC) resection specimens and provide a thorough histopathological evaluation of the cultures. Results: We show that we were able to establish organoid cultures of lung adenocarcinomas (LUADs) and lung squamous cell carcinomas (LUSCs) successfully, and that the organoid cultures of different subtypes of NSCLC preserved the histoarchitecture and growth pattern of the tumors they derive from. Immunohistochemistry and AB-PAS staining confirmed the subtype-specific protein expression pattern and preserved mucin production in LUAD organoids. The genetic abnormalities of the tumors assessed by immunohistochemistry (IHC-P) were preserved in the organoid cultures. Conclusions: Our thorough study reveals conserved PDTO histopathology, supports further exploration, and encourages using PDTO models in translational research projects. PDTO models hold remarkable promise as patient-specific models and may be applied to predict therapy response in cases where molecular–pathological analyses pose significant management dilemmas, and they also may provide a platform for exploring the molecular mechanisms of therapy resistance in a biologically relevant model system. Full article

The real-time surface thermal monitoring of thermal protection structures (TPSs) is crucial for hypersonic vehicle safety. This study proposes an effective approach for real-time temperature reconstruction by integrating embedded sensor arrays with an enhanced full-time domain inversion algorithm, utilizing the overlapping sliding window method. An array of three evenly spaced sensors is used for TPS monitoring. Notably, the inversion approach eliminates the need for prior knowledge of the TPS’s thermal parameters. It exhibits remarkable practicality with low-frequency sampling requirements (1 Hz) and robust noise resistance. Through numerical simulations and a quartz lamp side heating experiment, it is demonstrated that the window size and data noise have great influence on the temperature reconstruction accuracy, but the window slip step has little influence. The mean relative error of the inversion temperature decreases exponentially as the window size increases, and the optimal window duration is equal to the thermal hysteresis time. The study investigates the impact of three noise filtering methods on the inversion accuracy, finding that the Savitzky-Golay filtering significantly enhances measurement precision, reducing mean relative error from 18.4% to 6.7%. These results highlight the potential of the proposed real-time sensor method for practical engineering applications, offering a reliable and efficient solution for real-time TPS temperature monitoring. Full article

In this study, a quenching experiment was conducted at atmospheric pressure to investigate the flow and heat-transfer characteristics of cylindrical rods made from SS, FeCrAl, and Zr-4 under various subcooling degrees (ΔT_sub). The inverse heat-conduction problem (IHCP) method and image-processing technique were utilized to determine the surface temperature and heat flux, vapor film thickness, and quench front propagation. The results show that smaller solid kρc_p and larger ΔT_sub result in relatively more efficient quenching boiling heat transfer, thinner vapor film thickness, and greater quench front propagation velocity. The quench front originates at the bottom of the test specimen and becomes progressively larger in velocity with time. It eventually converges with the downward-propagating quench front in the upper middle of the test specimen. Moreover, at the beginning of quench front propagation, the SS and FeCrAl test specimens have a constant velocity region. However, because the Zr-4 test specimen has a small kρc_p, the velocities gradually increase from the onset of quench front generation. Furthermore, the measured average quench front velocities are consistent with the experimental datum from the literature. However, the predicted model proposed by Duffey underestimates the propagation velocity due to ignoring the cooling effect of film boiling. Full article

Thermally characterizing high-thermal conductivity materials is challenging, especially considering high temperatures. However, the modeling of heat transfer processes requires specific material information. The present study addresses an inverse approach to estimate the thermal conductivity of SAE 1020 relative to temperature during an autogenous LASER Beam Welding (LBW) experiment. The temperature profile during LBW is computed with the aid of an in-house CUDA-C algorithm. Here, the governing three-dimensional heat diffusion equation is discretized through the Finite Volume Method (FVM) and solved using the Successive Over-Relaxation (SOR) parallelized iterative solver. With temperature information, one may employ a minimization procedure to assess thermal properties or process parameters. In this work, the Quadrilateral Optimization Method (QOM) is applied to perform estimations because it allows for the simultaneous optimization of variables with no quantity restriction and renders the assessment of parameters in unsteady states valid, thereby preventing the requirement for steady-state experiments. We extended QOM’s prior applicability to account for more parameters concurrently. In Case I, the optimization of the three parameters that compose the second-degree polynomial function model of thermal conductivity is performed. In Case II, the heat distribution model’s gross heat rate (Ω) is also estimated in addition to the previous parameters. Ω [W] quantifies the power the sample receives and is related to the process’s efficiency. The method’s suitability for estimating the parameters was confirmed by investigating the reduced sensitivity coefficients, while the method’s stability was corroborated by performing the estimates with noisy data. There is a good agreement between the reference and estimated values. Hence, this study introduces a proper methodology for estimating a temperature-dependent thermal property and an LBW parameter. As the performance of the present algorithm is increased using parallel computation, a pondered solution between estimation reliability and computational cost is achieved. Full article

In this work, the effects of jet impact angle and water flow on the heat-transfer coefficient in boron steel probes were analyzed. Angles of 90°, 75° and 60° were used with stirring flows of 33 l·min⁻¹, 25 l·min⁻¹, 13 l·min⁻¹ and 6 l·min⁻¹. The aim consisted of determining the heat-extraction rates by analyzing the correlation programmed in the Ansys Fluent 2020R2 software when different cooling conditions are used, avoiding many experiments, and establishing quenching conditions free of surface defects on the workpiece. This process is currently used in heavy machinery, requiring high hardness and wear resistance. The fluid-dynamic field was validated using a scale physical model using the particle image velocimetry technique, PIV. In contrast, the thermal field was validated with transient state experiments solving the inverse heat conduction problem, IHCP. The results show that for high flows (33 l·min⁻¹), the jets with an angle of 90° impact the entire surface of the piece, but their cooling rate is slower compared to the other angles, being 243.61 K·s⁻¹, and 271.70 K·s⁻¹, 329.56 K·s⁻¹ for 75° and 60°, respectively. However, for low flows (6 l·min⁻¹), the impact velocities are very similar for the three cases, promoting more homogeneous cooling rates of 58.47 K·s⁻¹, 73.58 K·s⁻¹ and 63.98 K s⁻¹ for angles of 90°, 75° and 60°, respectively. Likewise, through the use of CCT diagrams, it was determined that regardless of the cooling rate, the final structure will always be a mixture of martensite–bainite due to the effect of boron as determined experimentally, which implies a more significant proportion of martensite at higher cooling rates. Full article

The type VI secretion system (T6SS) is a large secretory device, widely found in Gram-negative bacteria, which plays important roles in virulence, bacterial competition, and environmental adaptation. Vibrio alginolyticus (V. alginolyticus) is an opportunistic pathogen that causes vibriosis in aquaculture animals. V. alginolyticus possesses two type VI secretion systems (named the T6SS1 and T6SS2), but their functions remain largely unclear. In this paper, the roles of the core component of the T6SS2 cluster of V. alginolyticus HY9901, hemolysin-coregulated protein2 coding gene hcp2, are reported. Deletion of hcp2 clearly impaired the swarming motility, adhesive capacity, and pathogenicity of V. alginolyticus against zebrafish. Furthermore, transmission electron microscopy (TEM) found that the abnormal morphology of flagellum filament in the hcp2 mutant strain could be partially restored by hcp2 complementarity. By proteomic and RT-qPCR analysis, we confirmed that the expression levels of flagellar flagellin and assembly-associated proteins were remarkably decreased in an hcp2 mutant strain, compared with the wild-type strain, and could be partially restored with a supply of hcp2. Accordingly, hcp2 had a positive influence on the transcription of flagellar regulons rpoN, rpoS, and fliA; this was verified by RT-qPCR. Taken together, these results suggested that hcp2 was involved in mediating the motility, adhesion, and pathogenicity of Vibrio alginolyticus through positively impacting its flagellar system. Full article

During high-pressure die casting, a significant amount of heat is dissipated via the liquid-cooled channels in the die. The jet cooler, also known as the die insert or bubbler, is one of the most commonly used cooling methods. Nowadays, foundries casting engineered products rely on numerical simulations using commercial software to determine cooling efficiency, which requires precise input data. However, the literature lacks sufficient investigations to describe the spatial distribution of the heat transfer coefficient in the jet cooler. In this study, we propose a solver using the open-source CFD package OpenFOAM and free library for nonlinear optimization NLopt for the inverse heat conduction problem that returns the desired distribution of the heat transfer coefficient. The experimental temperature measurements using multiple thermocouples are considered the input data. The robustness, efficiency, and accuracy of the model are rigorously tested and confirmed. Additionally, temperature measurements of the real jet cooler are presented. Full article

The total heat exchange factor is one of the most important thermal physical parameters in the heat transfer model for a reheating furnace machine. In this paper, a novel general strategy, which is combined with the first-optimize-then-discretize (FOTD) approach and an improved hybrid conjugate gradient (IHCG) algorithm, is proposed to identify the total heat exchange factor by solving a nonlinear inverse heat conduction problem (IHCP). Firstly, a nonlinear IHCP with the Dirichlet-type boundary condition $T_m\left(t\right)=T(0,t)$ is built to determine the unknown total heat exchange factor $w\left(t\right)$. Secondly, the analysis of the Fréchet gradient of the cost functional is given and the gradient is proved as Lipschitz continuous by the FOTD approach. Thirdly, based on the gradient information by FOTD, a new IHCG algorithm, whose global convergence is proved by us, is proposed for fast solving of the optimization problem. Finally, simulation experiments are given to verify the effectiveness of the proposed strategy. Compared with the first-discretize-then-optimize (FDTO) approach, the FOTD approach can reduce running time and iteration number. Compared with other CG algorithms, the proposed IHCG algorithm has better convergence performance. The experimental data by the thermocouples experiments from a reheating furnace are also given to identify the total heat exchange factor. Full article

Globally, Antibiotic resistance is a major public health concern, with antibiotic use contributing significantly. Targeting informal healthcare providers (IHCPs) is important to achieve universal health coverage and effective antibiotic stewardship in resource-constrained settings. We, therefore, aimed to analyse the internal and external drivers that influence IHCPs’ prescribing behaviour for common illnesses in children under five, with an emphasis on antibiotic use in rural areas of India. A total of 48 IHCPs participated in focus group discussions. Thematic framework analysis with an inductive approach was used, and findings were collated in the theoretical framework based on knowledge, attitude, and practice model which depicted that the decisions made by IHCPs while prescribing antibiotics are complex and influenced by a variety of external and internal drivers. IHCPs’ internal drivers included the misconception that it is impossible to treat a patient without antibiotics and that antibiotics increase the effectiveness of other drugs and cure patients faster in order to retain them. Formal healthcare providers were the IHCPs’ sources of information, which influences their antibiotic prescribing. We found when it comes to seeking healthcare in rural areas, the factors that influence their choice include ‘rapid cure’, ‘cost of treatment’, ‘distance’ and ‘24 h availability’, instead of qualification, which may create pressure for IHCPs to provide a quick fix. Targeted and coordinated efforts at all levels will be needed to change the antibiotic prescribing practices of IHCPs with a focus on behaviour change and to help resolve misconceptions about antibiotics. Full article

Antibiotic misuse is one of the major drivers of antimicrobial resistance (AMR). In India, evidence of antibiotic misuse comes largely from retailers as well as formal and informal healthcare providers (IHCPs). This paper presents the practices and perspectives of drug wholesalers, a critical link between manufacturers and last-mile dispensers. Four experienced wholesalers and an ex-State Drug Controller (ex-SDC) were interviewed in depth, using semi-structured guides in the National Capital Region of Delhi, India, between November 2020 and January 2021. Four main findings were that wholesalers (i) have limited knowledge about wholesale licensing and practice regulations, as well as a limited understanding of AMR; (ii) directly supply and sell antibiotics to IHCPs; (iii) facilitate medical representatives (MRs) of pharmaceutical companies and manufacturers in their strategies to promote antibiotics use in the community; and (iv) blame other stakeholders for unlawful sale and overuse of antibiotics. Some of the potential solutions aimed at wholesalers include having a minimum education qualification for licensing and mandatory Good Distribution Practices certification programs. Decoupling incentives by pharmaceutical companies from sales targets to improve ethical sales practices for MRs and optimize antibiotic use by IHCPs could alleviate wholesalers’ indirect actions in promoting antibiotic misuse. Full article