Resistor Network Research Articles

New Antimicrobial Resistance Strategies: An Adaptive Resistance Network Conferring Reduced Glycopeptide Susceptibility in VISA.

Background: Vancomycin-intermediate Staphylococcus aureus (VISA) emerges typically in the healthcare-associated methicillin-resistant S. aureus and more rarely in community-acquired S. aureus (CA-MRSA). VISA is a serious concern for public health due to its association with persistent infections, the failure of vancomycin treatment, and poor clinical outcomes. Currently, the burden of VISA is somewhat high, even though vancomycin is the mainstay treatment for severe MRSA infections. The molecular mechanisms of reduced glycopeptide susceptibility in S. aureus are constantly under investigation but have still not yet been fully characterized. Methods: Our goal was to investigate the reduced glycopeptide susceptibility mechanisms emerging in a VISA CA-MRSA versus its vancomycin-susceptible (VSSA) CA-MRSA parents in a hospitalized patient undergoing glycopeptide treatment. Comparative integrated omics, Illumina MiSeq whole-genome sequencing (WGS), RNA-Seq, and bioinformatics were performed. Results: Through a comparison of VISA CA-MRSA vs. its VSSA CA-MRSA parent, mutational and transcriptomic adaptations were found in a pool of genes involved, directly or indirectly, in the biosynthesis of the glycopeptide target conferring or supporting the VISA phenotype, and its cross-resistance with daptomycin. This pool included key genes responsible for the biosynthesis of the peptidoglycan precursors, i.e., D-Ala, the D-Ala-D-Ala dipeptide termini of the pentapeptide, and its incorporation in the nascent pentapeptide, as key targets of the glycopeptide resistance. Furthermore, accessory glycopeptide-target genes involved in the pathways corroborated the key adaptations, and thus, supported the acquisition of the VISA phenotype i.e., transporters, nucleotide metabolism genes, and transcriptional regulators. Finally, transcriptional changes were also found in computationally predicted cis-acting small antisense RNA triggering genes related both to the key or accessory adaptive pathways. Conclusion: Our investigation describes an adaptive resistance pathway acquired under antimicrobial therapy conferring reduced glycopeptide susceptibility in a VISA CA-MRSA due to a comprehensive network of mutational and transcriptional adaptations in genes involved in pathways responsible for the biosynthesis of glycopeptide's target or supporters of the key resistance path.

Realizing the Accurate Measurements of Thermal Conductivity over a Wide Range by Scanning Thermal Microscopy Combined with Quantitative Prediction of Thermal Contact Resistance.

Quantitative thermal performance measurements and thermal management at the micro-/nano scale are becoming increasingly important as the size of electronic components shrinks. Scanning thermal microscopy (SThM) is an emerging method with high spatial resolution that accurately reflects changes in local thermal signals based on a thermally sensitive probe. However, because of the unclear thermal resistance at the probe-sample interface, quantitative characterization of thermal conductivity for different kinds of materials still remains limited. In this paper, the heat transfer process considering the thermal contact resistance between the probe and sample surface is analyzed using finite element simulation and thermal resistance network model. On this basis, a mathematical empirical function is developed applicable to a variety of material systems, which depicts the relationship between the thermal conductivity of the sample and the probe temperature. The proposed model is verified by measuring ten materials with a wide thermal conductivity range, and then further validated by two materials with unknown thermal conductivity. In conclusion, this work provides the prospect of achieving quantitative characterization of thermal conductivity over a wide range and further enables the mapping of local thermal conductivity to microstructures or phases of materials.

Thermal-hydraulic model for temperature prediction on oil-directed power transformers

The temperatures of a power transformer have direct influence on the windings insulation deterioration, determining how long the equipment will be able to remain in operation. In order to better predict and study the transformer thermal behavior, a thermal-hydraulic model (TH) for oil-directed (OD) power transformer is proposed. From the constructive dimensions and the operative characteristics of the transformer, the proposed model is able to determine the complete oil flow and temperature distributions over the magnetic core, windings and radiators by iteratively solving an algorithm composed of both hydraulic and thermal resistance networks. A transformer prototype was assembled and equipped with 29 optical fiber sensors as part of a measurement system in order to validate the approach. The details of the active part, tank and radiators modelings are presented in a generalized way, being applicable to different constructive arrangements. The validation results show a maximum relative error of 1.31% for temperature, accurately describing the flow and temperature fields of the prototype, indicating that the model can be satisfactorily used for predicting the hydraulic and thermal behaviors of electric transformers.

The transient invisibility cloak in the electro-quasi-static field

The invisibility condition of cloak in the Electro-Quasi-Static (EQS) field under the arbitrary transient excitation is given in this paper. Firstly, because electric field with magnetoelectric effect ignored can be attributed to the EQS field which is the transient electric field. In this case, the analytical invisibility conditions of infinite length coaxial cylinders cloaks under arbitrary transient excitation are derived in the EQS field. Then, by the finite element method(FEM) simulation, the correctness of the analytical invisibility condition is verified. Besides, this paper also established the equivalent circuit model for the cloak in the EQS field by the resistance and capacitance network. At last, analytical invisibility conditions of the concentric spheres cloak are also given. By the invisibility conditions proposed in this paper, the cloak could achieve stealth under the transient electric field which will greatly enhance the performance of the cloak.

Multi-objective optimisation of thermal and hydraulic performance with various concentrations of hybrid Fe3O4/graphene nanofluids in a microchannel heat sink

An accurate thermal resistance network and an objective function of pressure drop were established for a microchannel heat sink (MCHS) to evaluate the heat transfer and hydraulic performance of hybrid Fe3O4/graphene nanofluids with different concentrations in the MCHS. An optimised geometry of the MCHS with nanofluids at 40 °C under mass concentrations of 0.1, 0.3, and 0.5 wt% was obtained through multi-objective particle swarm optimisation (MOPSO). By using the K-means clustering method, a Pareto front of an optimised solution set was divided into three clustering zones with the optimal heat transfer performance, balanced performance, and optimal hydraulic performance. Combined with a comprehensive enhanced heat transfer factor, suggestions for trade-off in these three zones were proposed. The results indicate that the hybrid Fe3O4/graphene nanofluids is an attractive heat transfer medium in the MCHS and the optimised dimensions obtained by the MOPSO can simultaneously reduce the thermal resistance and pressure drop across the MCHS. Nanofluids with higher concentrations can amplify the effects of reducing the thermal resistance without increasing the loss of pumping power when the working temperature of the MCHS increases. The increase in the concentration of nanofluids can constantly decrease the dimensions of the MCHS in the Pareto front. Therefore, ensuring the stability of nanofluids can prevent the resulting pseudo-high concentration from influencing the accuracy of optimisation data.

Abstract 1084: AI-aided drug development for disconnecting glioma tumor microtube networks

Abstract Diffuse infiltrating gliomas, especially glioblastomas, are the most common incurable primary brain tumors in adults. The aggressive growth and high resistance against cytotoxic agents are mediated by ultra-long tubular membrane protrusions, Tumor Microtubes (TMs), that interconnect single glioblastoma cells via gap junctions to multicellular communicating and resistant networks. Early studies showed that targeting these malignant networks increases response to therapy. Thus, the disconnection of such networks has emerged as a new therapeutic strategy to decrease radioresistance. However, the development of drugs that interfere with TM- and network formation is compromised by the lack of established drug screening pipelines to study a compound‘s specific anti-TM and network-inhibiting activity in combination with radiotherapy. To identify compounds with anti-TM activity, we first developed an in vitro medium-throughput imaging-based drug screening. Human-derived primary glioblastoma cells were seeded in a newly developed 2D monolayer where tumor cells form TMs and networks. The cells were treated with compounds with potential anti-TM activity. Using high-resolution laser scanning microscopy, morphological readouts were obtained and analyzed. The most promising compounds were then evaluated in a xenograft chronic cranial window mouse model. Treatments were administered with concomitant radiotherapy (6Gy per day for 3 days). By observing TM and tumor cell network changes via longitudinal in vivo 2-photon microscopy, tumor cell count, growth, and TM parameters were measured in the live mouse over up to 12 weeks. Among the 87 compounds tested in vitro, 42 significantly inhibited TMs. Two of these hits showed a higher count of dead cells in combination with radiotherapy as opposed to glioblastoma cells treated with radiotherapy alone and were therefore studied in the in vivo pipeline. One of these two agents showed reductions of TM length and striking responses in a combinatorial treatment regime with radiotherapy in individual mice that were not observed in control animals treated with radiotherapy only; however, the responses observed were heterogeneous between regions and mice. Further studies revealed this compound directly phosphorylates the gap junction protein Connexin 43 on S368, which contributes to a decrease in intercellular communication of glioblastoma cells. By applying different imaging techniques and AI algorithms we successfully established a novel in-vitro-to-in-vivo drug screening pipeline for the development of disconnecting agents. Most importantly, our data shows that disconnecting multicellular brain tumor networks increases response to radiotherapy. Further studies will be needed to develop reliable anti-TM agents as novel co-treatment options to sensitize glioblastomas to cytotoxic therapy. Citation Format: Daniel D. Azorín, Sophie Weil, Dirk C. Hoffmann, David Hausmann, Erik Jung, Matthias Osswald, Jill Reckless, Nigel Ramsden, Simon Thompson, David Grainger, Wolfgang Wick, Frank Winkler. AI-aided drug development for disconnecting glioma tumor microtube networks [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1084.

SF-SGL: Solver-Free Spectral Graph Learning From Linear Measurements

This work introduces a highly-scalable spectral graph densification framework (SGL) for learning resistor networks with linear measurements, such as node voltages and currents. We show that the proposed graph learning approach is equivalent to solving the classical graphical Lasso problems with Laplacian-like precision matrices. We prove that given $O(\log N)$ pairs of voltage and current measurements, it is possible to recover sparse $N$-node resistor networks that can well preserve the effective resistance distances on the original graph. In addition, the learned graphs also preserve the structural (spectral) properties of the original graph, which can potentially be leveraged in many circuit design and optimization tasks. To achieve more scalable performance, we also introduce a solver-free method (SF-SGL) that exploits multilevel spectral approximation of the graphs and allows for a scalable and flexible decomposition of the entire graph spectrum (to be learned) into multiple different eigenvalue clusters (frequency bands). Such a solver-free approach allows us to more efficiently identify the most spectrally-critical edges for reducing various ranges of spectral embedding distortions. Through extensive experiments for a variety of real-world test cases, we show that the proposed approach is highly scalable for learning sparse resistor networks without sacrificing solution quality. We also introduce a data-driven EDA algorithm for vectorless power/thermal integrity verifications to allow estimating worst-case voltage/temperature (gradient) distributions across the entire chip by leveraging a few voltage/temperature measurements.

Design of High Performance and Power Efficient Flash ADC

In this paper, Flash Analog to digital converter is implemented. The designed Flash ADC consists of a resistive ladder network, comparators, the thermometer to a binary encoder and the entire design is carried out using Tanner tools employing 180nm technology. The reference voltage applied to the resistive ladder network is 1.8V. A two-stage operational amplifier is used as a comparator in the flash ADC. Here, we are modifying the structure of operational Amplifier using Power Gating Technique. Binary code is obtained from the thermometer code by utilizing a Mux based encoder by designing the MUX in domino Logic. The major problem that usually appears in flash ADC is as the number of resolution bits increases, the Area, as well as the power consumption of the circuit, also increases. In this paper, we principally concentrated to lessen the propagation delay of the ADC by optimizing encoder circuitry. With the purpose of reducing latency, Encoder is implemented using 2:1 mux based on Pseudo NMOS Logic. Performance parameters of Flash ADC such as delay as well as average power are calculated and compared.

Deterministic entanglement distribution on series-parallel quantum networks

The performance of distributing entanglement between two distant nodes in a large-scale quantum network (QN) of partially entangled bipartite pure states is generally benchmarked against the classical entanglement percolation (CEP) scheme. Improvements beyond CEP were only achieved by nonscalable strategies for restricted QN topologies. This paper explores and amplifies a new and more effective mapping of a QN, referred to as concurrence percolation theory (ConPT), that suggests using deterministic rather than probabilistic protocols for scalably improving on CEP across arbitrary QN topology. More precisely, we implement ConPT via a deterministic entanglement transmission (DET) scheme that is fully analogous to resistor network analysis, with the corresponding series and parallel rules represented by deterministic entanglement swapping and concentration protocols, respectively. The main contribution of this paper is to establish a powerful mathematical framework, which is applicable to arbitrary $d$-dimensional information carriers (qudits), that provides different natural optimality metrics in terms of generalized $k$-concurrences (a family of fundamental entanglement measures) for different QN topologies. In particular, we conclude that the introduced DET scheme (a) is optimal over the well-known nested repeater protocol for distilling entanglement from partially entangled qubits and (b) leads to higher success probabilities of obtaining a maximally entangled state than using CEP. The implementation of the DET scheme is experimentally feasible as tested on IBM's quantum computation platform.

The juggernaut endures: protest, Potemkinism, and Olympic reform

ABSTRACT Mega-events like the Olympics and the Football World Cup routinely harm host cities and societies, largely due to their linkages with ambitious urban development agendas. Concurrently, resident protest has had only limited success in mitigating mega-event-related damages, notwithstanding the growth of resistance networks at local, national, and transnational scales. Contextualised within the broader processes of the Agenda 2020 and New Norm Olympic reforms, this paper explores the tactics of protest against the Summer Olympics in Paris 2024 and Los Angeles 2028. In so doing, the paper demonstrates how the reforms have moderated some of the more egregious aspects of mega-event harm, while nevertheless preserving some fundamental problems with hosting, albeit in more diffuse or disguised forms. The paper makes sense of these processes through the notion of Potemkinism, conceptualised as a dynamic between the superficial and the substantive, and predicated on obfuscation or concealment. The paper also presents a taxonomy of tactics adopted by host city residents to counter the problems that persist in these processes of Potemkin reform.

Transcriptomic and functional analyses reveal the molecular mechanisms underlying Fe-mediated tobacco resistance to potato virus Y infection.

Potato virus Y (PVY) mainly infects Solanaceous crops, resulting in considerable losses in the yield and quality. Iron (Fe) is involved in various biological processes in plants, but its roles in resistance to PVY infection has not been reported. In this study, foliar application of Fe could effectively inhibit early infection of PVY, and a full-length transcriptome and Illumina RNA sequencing was performed to investigate its modes of action in PVY-infected Nicotiana tabacum. The results showed that 18,074 alternative splicing variants, 3,654 fusion transcripts, 3,086 long non-coding RNAs and 14,403 differentially expressed genes (DEGs) were identified. Specifically, Fe application down-regulated the expression levels of the DEGs related to phospholipid hydrolysis, phospholipid signal, cell wall biosynthesis, transcription factors (TFs) and photosystem I composition, while those involved with photosynthetic electron transport chain (PETC) were up-regulated at 1 day post inoculation (dpi). At 3 dpi, these DEGs related to photosystem II composition, PETC, molecular chaperones, protein degradation and some TFs were up-regulated, while those associated with light-harvesting, phospholipid hydrolysis, cell wall biosynthesis were down-regulated. At 9 dpi, Fe application had little effects on resistance to PVY infection and transcript profiles. Functional analysis of these potentially critical DEGs was thereafter performed using virus-induced gene silencing approaches and the results showed that NbCat-6A positively regulates PVY infection, while the reduced expressions of NbWRKY26, NbnsLTP, NbFAD3 and NbHSP90 significantly promote PVY infection in N. benthamiana. Our results elucidated the regulatory network of Fe-mediated resistance to PVY infection in plants, and the functional candidate genes also provide important theoretical bases to further improve host resistance against PVY infection.

Dependence of hopping electrical resistivity on concentration and localization radius, simulation study

The exponential dependence of resistivity on concentration and on electron localization radius in hopping electron transport is of special significance. It is the main clue in favor of hopping conductance mechanism. This dependence was studied experimentally, theoretically and in simulations. So far, the simulations were carried out in the Miller–Abrahams resistor network approximation. In this work, a more precise simulation is presented, which takes into account electron correlations in a fully connected network of sites, and achieves averaging by simulation of supercells. Although occasionally a quantitative agreement with existing reports is achieved, the excellent agreement between the percolation theory and some existing simulations, is a coincidence. The new results are interpreted using percolation theory. There are indications on the important role of the prefactor of resistivity in interpreting the slope of the semi-logarithmic plot of resistivity vs average separation of localization sites. The influence of the finite temperature is investigated. The simulations are carried out assuming a doped crystalline semiconductor as the hopping medium, however the results are applicable to other systems with the identical dependencies of the hopping rate on hopping distance.

Spectral techniques and mathematical aspects of K 4 chain graph

The resistance distance between any two vertices of a connected graph is defined as the net effective resistance between them. An electrical network can be constructed from a graph by replacing each edge with a unit resistor. Resistance distances are computed by methods of the theory of resistive electrical networks (based on Ohm’s and Kirchhoff’s laws). The standard method to compute resistance distance is via the Moore-Penrose generalized inverse of the Laplacian matrix of the underlying graph G. In this article, we used the electric network approach and the combinatorial approach, to derive the exact expression for resistance distances between any two vertices of the ring model. By employing a recursive connection, firstly we determined all the eigenvalues and their multiplicities in relation to the corresponding Laplacian and normalised matrices. Secondly, we obtained the Kirchhoff index and multiplicative degree Kirchhoff index for . Finally, we calculated the mean first passage time and Kemeny constant of . Our computed results provide a comprehensive approach for exploring random walks on complex networks, especially biased random walks, which may also help to better understand and tackle some practical problems such as search and routing on networks.

NS-GAAFET Compact Modeling: Technological Challenges in Sub-3-nm Circuit Performance

NanoSheet-Gate-All-Around-FETs (NS-GAAFETs) are commonly recognized as the future technology to push the digital node scaling into the sub-3 nm range. NS-GAAFETs are expected to replace FinFETs in a few years, as they provide highly electrostatic gate control thanks to the GAA structure, with four sides of the NS channel entirely enveloped by the gate. At the same time, the NS rectangular cross-section is demonstrated to be effective in its driving strength thanks to its high saturation current, tunable through the NS width used as a design parameter. In this work, we develop a NS-GAAFET compact model and we use it to link peculiar single-device parameters to digital circuit performance. In particular, we use the well-known BSIM-CMG core solver for multigate transistors as a starting point and develop an ad hoc resistive and capacitive network to model the NS-GAAFET geometrical and physical structure. Then, we employ the developed model to design and optimize a digital inverter and a five-stage ring oscillator, which we use as a performance benchmark for the NS-GAAFET technology. Through Cadence Virtuoso SPICE simulations, we investigate the digital NS-GAAFET performance for both high-performance and low-power nodes, according to the average future node present in the International Roadmap for Devices and Systems. We focus our analysis on the main different technological parameters with regard to FinFET, i.e., the inner and outer spacers. Our results highlight that in future technological nodes, the choice of alternative low-K dielectric materials for the NS spacers will assume increasing importance, being as relevant, or even more relevant, than photolithographic alignment and resolution at the sub-nm scale.

Thermal conduction model of asymmetric structural aramid nanofiber aerogel membranes based on fractal theory

Asymmetric structural aramid nanofiber aerogel membranes (ASAAMs) have been considered ideal thermal insulators due to their unique characteristics, such as dense surface layers and nanoscale 3D fibrous body components. Fractal theory has been used in studying the pore size distribution of fibrous aerogels with symmetrical structures but is rarely used in studying the thermal conductivity of asymmetric structural aerogels. In this work, two basic fractal units are used to simulate the pore size distribution of ASAAMs. The models are transformed into series and parallel fractal resistance networks using the equivalent resistance method. Additionally, a marginal weighting function is proposed to modify the heat transfer model, which is applied to calculate the total effective thermal conductivity of ASAAMs. Results showed that: (1) The correlation between the porosity and the effective thermal conductivity of ASAAMs is negative. (2) The basic fractal units of 7 × 7 size selected in this paper could be described the pore size distribution of ASAAMs well. (3) The modified model demonstrates only 2.58% error, which is closer to the experimental data.

Electrical property of an m × n apple surface network

The circuit network model has important application value in many disciplines, and many complex problems can be simulated by establishing the network model. However, looking for the explicit solutions of the electrical property in an arbitrary resistor network is important but difficult. In this paper an arbitrary m × n apple surface network is researched by the Recursion-Transform method with voltage parameters (RT-V) for the first time, and the RT-V method consists of four rigorous basic steps. We study and derive the exact analytical expression of potential function and the equivalent resistance formula, and some special cases and applications of them are also discussed. The theoretical results obtained are concise and provide a new theoretical basis for the research of related subjects.

Simplified Calculation Model for Contact Resistance Based on Fractal Rough Surfaces Method

Electrical contact resistance (ECR) is critical to evaluate the stability and reliability of electrical connections. In this paper, a simplified contact model is established for rough surfaces based on the fractal theory and Monte Carlo method, which can overcome the difficulty of constructing the resistance networks for traditional contact models. The model reveals the influence of fractal parameters D and G on the surface morphology and contact characteristics. The established surface method can simulate Gaussian and non-Gaussian isotropic surfaces. Then the contact resistance considering a contaminated film is calculated, which provides a quantitative analysis of the change and the influencing factors. The accuracy of the calculation method in this paper is ensured by comparing the existing experimental data and finite element results. The results show that the contact surface with D of 1.5 has the largest real contact area and the smallest contact resistance. The model has accurate calculation results when dimensionless contact load F* is less than 4 × 10−3.

Network biology of lapatinib resistance in different types of HER2-positive breast cancers informs the prioritization of the combination anticancer treatments as anti-resistance interventions

Background: With widespread therapeutic advancement, targeted anticancer therapeutics are taking over traditional treatment protocols. Nevertheless, the resistance to targeted therapeutics has halted the enthusiastic treatment response. An example of targeted therapy is Lapatinib. Lapatinib is a tyrosine kinase inhibitor used in HER2-positive breast cancer. It is widely used in HER2-positive metastatic breast cancer in combination with other drugs. Methods: This study's main objective was to provide a plausible mechanistic insight into lapatinib’s resistance in two HER2 positive breast cancer cell lines, SKBR3 and BT-474. We performed gene set analysis to identify the differentially expressed genes (DEG) in response to treatment with lapatinib from the gene expression profiles obtained from GSE38376 and GSE16179. The DEG was then analyzed by Ingenuity Pathway Analysis (IPA). Results: The IPA analysis showed that the increased expression of Hypoxia-inducible factor-1 alpha (HIF-1α) and Wnt/β-catenin and their related networks were associated with resistance and poor prognosis in SKBR3 and BT-474 cell lines, respectively. Although both cell lines are categorized as HER2 positive cell lines and in some reports were used interchangeably, in our hands, the two cell lines exhibited different biological pathways underlying resistance to lapatinib. In addition, among the other top canonical pathways, TNF was identified as the top upstream regulator in SKBR3 cell lines, whereas the Microphthalmia-associated transcription factor (MITF) was predicted as a top regulator in BT-474 cell lines. Conclusions: This study highlights the relevance of HIF-1α and Wnt/β-catenin compensatory networks in resistance toward lapatinib. Our findings outline the activation of angiogenesis and invasion processes in resistant cells with differential underlining gene networks in two different HER2 positive cell lines. The two cell lines reflect two different types of breast cancer, and hence the treatment strategy to avoid resistance should be planned differently.

Theoretical modeling for piezoresistive behavior of aligned carbon nanotube/polymer nanocomposites accounting for evolution of agglomerates morphology

In this study, the electromechanical response of carbon nanotube (CNT)-reinforced polymer nanocomposites subjected to uniaxial deformation was investigated theoretically. For this purpose, a comprehensive analytical model that incorporated critical factors affecting the piezoresistive properties of CNT/polymer nanocomposites was proposed. To determine the effects of field-induced CNT alignment and the corresponding prolonged agglomeration morphology, an effective resistor network was established to predict piezoresistivity defined as the normalized resistance change of CNT/polymer nanocomposites. The proposed model accurately described the piezoresistive properties of randomly aligned CNT-based composites compared with a previously developed model, and its further validation was performed using experimental data obtained from the literature for CNTs aligned in a polymer matrix. A similar approach was used for the determination of a percolation threshold, which strongly correlated with piezoresistivity. In addition, the effect of each individual critical factor was examined to establish a desirable set of parameters that would either decrease the percolation threshold or increase the piezoresistivity of composites. • The theoretical model is proposed for the piezoresistive behavior of carbon nanotube (CNT)/polymer composites. • The effects of electric field-induced alignment of CNTs and their aggregation morphology have been taken into account. • An optimal set of critical parameters is determined to increase the piezoresistivity of CNT/polymer nanocomposites.

Thermal-oxidation coupled analysis method for unidirectional fiber-reinforced C/SiC composites in air oxidizing environments below 1000 °C

The thermal analysis method for unidirectional fiber-reinforced C/SiC composites (C/SiC-UFRC) in air oxidizing environment below 1000 °C is developed, including a mathematical theoretical model and a finite element model. The mathematical model (MM) is established by combining the thermal resistance network method and the oxidation kinetics theory. The influence of oxidation characteristics on C/SiC-UFRC axial thermal conductivity is firstly introduced into MM, which provides a reference for the theoretical calculation method of C/SiC-UFRC axial thermal conductivity under oxidation conditions. The finite element model (FEM) is constructed on the representative volume element (RVE) of C/SiC-UFRC and the numerical heat transfer method. The FEM numerically simulated the microstructure in the oxidation process and firstly be applied to study the effects of oxidation on the micro temperature field and heat transfer of C/SiC-UFRC. Through the mutual confirmation of MM and FEM, the prediction of thermal conductivity of CMC in air oxidation environment is verified. The effects of oxidation time, oxidation temperature and random distribution of initial cracks are investigated to reveal their influences on the heat transfer behavior of C/SiC-UFRC.