Conjugate Calculation of Gas Turbine Vanes Cooled with Leading Edge Films

AbstractConjugate calculation methodology is used to simulate the C3X gas turbine vanes cooled with leading edge films of “shower-head” type. By comparing calculated results of different turbulence models with the measured data, it is clear that calculation with the transition model can better simulate the flow and heat transfer in the boundary layers with leading edge film cooling. In the laminar boundary layers, on the upstream suction side, the film cooling flow presents 3D turbulent characteristics before transition, which quickly disappear on the downstream suction side owing to its intensified mixing with hot gas boundary layer after transition. On the pressure side, the film cooling flow retains the 3D turbulent characteristics all the time because the local boundary layers' consistent laminar flow retains a smooth mixing of the cooling flow and the hot gas. The temperature gradients formed between the cooled metallic vane and the hot gas can improve the stability of the boundary layer flow because the gradients possess a self stable convective structure

IMECE2008-66575 THE KEY TECHNIQUES FOR THERMAL-FLOW-ELASTIC COUPLING NUMERICAL SIMULATION PLATFORM IN TURBINES

ABSTRACT Thermal-flow-elastic coupling(TFEC)numerical simulation platform has been an essential platform for designing turbo engines with high performance and efficiency. Generally, TFEC numerical simulation was achieved by predicting thermal and stress fields with finite element methods, while flow fields with finite difference methods, but such calculation was not popular in engineering design, because of too much size of data exchange and lower computing efficiency. However these shortcomings will not exist by using finite difference methods for all of the fields. To establish a three dimensional multifunction numerical simulation platform for turbines for all of the fields, the key technique was studied firstly. The technique included analysis on physical models, establishing of mathematical model equation, usage of curvilinear coordinate platform, construction of high accuracy difference scheme and selection of boundary conditions for multi-field coupling simulation. Then the algorithm including domain decomposition one and parallel one were studied to accelerate the coupling simulation. The purpose was to develop a completed TFEC numerical simulation platform by using of finite difference method and to apply the platform for numerical simulation in turbines. Firstly codes for predicting flow field in passage, thermal and stress fields in solid body were developed. Then a simple TFEC numerical simulation platform for turbines was obtained. The single code for predicting flow field was verified with experimental data, and the other two codes were validated with thermal and elastic analytic solutions respectively. And satisfying results were obtained. Then the code for thermal-flow was validated with experimental data of MarkⅡ blade, and the code for thermal-elastic coupling simulations was validated with a cylinder by an analytic solutions. All of these are good basics for completing TFEC numerical simulation platform using finite difference methods for all of the fields and computing TFEC numerical simulation in a turbo engine. INTRODUCTION Nowadays, the quick development of Aerospace Industries has been challenging the performance of aero-engine. To increase engine, reduce fuel consumption and improve engine efficiency, the turbine inlet temperature has to be greatly increased, the temperature of turbine blade that exceeds the acceptability of materials and is over melting point, and then it leads to a series of technological research. Hence cooling technique is required to lower the temperature of metallic materials and restrict the variety of temperature, to ensure the surface highest temperature of turbine blade and the largest gradient temperature to gear to the heat-stress of largest blade. Otherwise the traditional turbine design, with which the aerodynamic, thermal and elastic designs are carried out separately, is with a too long design circle, and it needs huge numerical and experimental resources. Consequently it is doubted to apply such technique into the design of turbines in the advanced engines. Therefore thermal-flow-elastic couplin

MONAI: An open-source framework for deep learning in healthcare

Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications of AI in healthcare have the potential to improve our ability to detect, diagnose, prognose, and intervene on human disease. For AI models to be used clinically, they need to be made safe, reproducible and robust, and the underlying software framework must be aware of the particularities (e.g. geometry, physiology, physics) of medical data being processed. This work introduces MONAI, a freely available, community-supported, and consortium-led PyTorch-based framework for deep learning in healthcare. MONAI extends PyTorch to support medical data, with a particular focus on imaging, and provide purpose-specific AI model architectures, transformations and utilities that streamline the development and deployment of medical AI models. MONAI follows best practices for software-development, providing an easy-to-use, robust, well-documented, and well-tested software framework. MONAI preserves the simple, additive, and compositional approach of its underlying PyTorch libraries. MONAI is being used by and receiving contributions from research, clinical and industrial teams from around the world, who are pursuing applications spanning nearly every aspect of healthcare.Comment: www.monai.i

Shifting the limits in wheat research and breeding using a fully annotated reference genome

Introduction: Wheat (Triticum aestivum L.) is the most widely cultivated crop on Earth, contributing about a fifth of the total calories consumed by humans. Consequently, wheat yields and production affect the global economy, and failed harvests can lead to social unrest. Breeders continuously strive to develop improved varieties by fine-tuning genetically complex yield and end-use quality parameters while maintaining stable yields and adapting the crop to regionally specific biotic and abiotic stresses. Rationale: Breeding efforts are limited by insufficient knowledge and understanding of wheat biology and the molecular basis of central agronomic traits. To meet the demands of human population growth, there is an urgent need for wheat research and breeding to accelerate genetic gain as well as to increase and protect wheat yield and quality traits. In other plant and animal species, access to a fully annotated and ordered genome sequence, including regulatory sequences and genome-diversity information, has promoted the development of systematic and more time-efficient approaches for the selection and understanding of important traits. Wheat has lagged behind, primarily owing to the challenges of assembling a genome that is more than five times as large as the human genome, polyploid, and complex, containing more than 85% repetitive DNA. To provide a foundation for improvement through molecular breeding, in 2005, the International Wheat Genome Sequencing Consortium set out to deliver a high-quality annotated reference genome sequence of bread wheat. Results: An annotated reference sequence representing the hexaploid bread wheat genome in the form of 21 chromosome-like sequence assemblies has now been delivered, giving access to 107,891 high-confidence genes, including their genomic context of regulatory sequences. This assembly enabled the discovery of tissue- and developmental stage–related gene coexpression networks using a transcriptome atlas representing all stages of wheat development. The dynamics of change in complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. Aspects of the future value of the annotated assembly for molecular breeding and research were exemplarily illustrated by resolving the genetic basis of a quantitative trait locus conferring resistance to abiotic stress and insect damage as well as by serving as the basis for genome editing of the flowering-time trait. Conclusion: This annotated reference sequence of wheat is a resource that can now drive disruptive innovation in wheat improvement, as this community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding. Importantly, the bioinformatics capacity developed for model-organism genomes will facilitate a better understanding of the wheat genome as a result of the high-quality chromosome-based genome assembly. By necessity, breeders work with the genome at the whole chromosome level, as each new cross involves the modification of genome-wide gene networks that control the expression of complex traits such as yield. With the annotated and ordered reference genome sequence in place, researchers and breeders can now easily access sequence-level information to precisely define the necessary changes in the genomes for breeding programs. This will be realized through the implementation of new DNA marker platforms and targeted breeding technologies, including genome editing

Optimization Design Method for Non-Rectangular Constant Stress Accelerated Testing Considering Parameter Estimation Precision

In addressing the design challenges for constant-stress accelerated life testing in non-rectangular experimental domains, we aim to optimize the precision in estimating parameters for the product reliability statistical model. Following the principles of regression orthogonal design theory to determine the combinations of stress levels, we constrain the maximum stress levels of each experimental stress along the boundary curve of the non-rectangular experimental domain. The remaining stress levels and the allocation ratios of specimens for each test serve as design variables in the optimization process. We establish a mathematical model for the optimal design of constant-stress accelerated life testing in non-rectangular experimental domains. The results of the optimized design for comprehensive stress accelerated life testing in non-rectangular experimental regions of aerospace electrical connectors indicate that, with the same sample size, the optimized testing scheme not only enhances the precision of model parameter estimation but also reduces the number of required tests. At an equivalent number of tests and testing duration, the optimization scheme proposed in this study demonstrates an improvement of over 63% in the precision of model parameter estimation compared to the EM-optimized testing scheme in non-rectangular experimental regions. Using the mean, standard deviation, and coefficient of variation of the determinant values of the information matrix as criteria for evaluating the precision and robustness of experimental designs, a simulated evaluation was conducted for the optimized experimental design, a conventional experimental design, and an EM experimental design. The results indicate that the optimal experimental design outperforms both the conventional experimental design and the EM experimental design in terms of precision and robustness