Limits of NbTi and Nb3Sn, and development of W& R Bi-2212 High Field Accelerator Magnets

NbTi accelerator dipoles are limited to magnetic fields (H) of about 10 T, due to an intrinsic upper critical field (H{sub c2}) limitation of 14 T. To surpass this restriction, prototype Nb{sub 3}Sn magnets are being developed which have reached 16 T. We show that Nb{sub 3}Sn dipole technology is practically limited to 17 to 18 T due to insufficient high field pinning, and intrinsically to 20 to 22 T due to H{sub c2} limitations. Therefore, to obtain magnetic fields approaching 20 T and higher, a material is required with a higher H{sub c2} and sufficient high field pinning capacity. A realistic candidate for this purpose is Bi-2212, which is available in round wires and sufficient lengths for the fabrication of coils based on Rutherford-type cables. We initiated a program to develop the required technology to construct accelerator magnets from 'wind-and-react' (W&R) Bi-2212 coils. We outline the complications that arise through the use of Bi-2212, describe the development paths to address these issues, and conclude with the design of W&R Bi-2212 sub-scale magnets

Development of Wind-and-React Bi-2212 Accelerator Magnet Technology

We report on the progress in our R&D program, targeted to develop the technology for the application of Bi{sub 2}Sr{sub 2}CaCu{sub 2}O{sub x} (Bi-2212) in accelerator magnets. The program uses subscale coils, wound from insulated cables, to study suitable materials, heat treatment homogeneity, stability, and effects of magnetic field and thermal and electro-magnetic loads. We have addressed material and reaction related issues and report on the fabrication, heat treatment, and analysis of subscale Bi-2212 coils. Such coils can carry a current on the order of 5000 A and generate, in various support structures, magnetic fields from 2.6 to 9.9 T. Successful coils are therefore targeted towards a hybrid Nb{sub 3}Sn-HTS magnet which will demonstrate the feasibility of Bi-2212 for accelerator magnets, and open a new magnetic field realm, beyond what is achievable with Nb{sub 3}Sn

Uncertainty quantification via elicitation of expert judgements

The purpose of this paper is to depict one method of quantifying uncertainty about different parameters, which is based on eliciting judgements either from a single expert or from a group of experts. The quantities obtained as a result of the elicitation are therefore used in order to fit probability density functions (PDFs) by using an in-house MATLAB model which uses appropriate fitting techniques similar to the ones suggested in the existing literature. Consequently, an initial framework has been implemented which would first of all allow the comparison of elicited data with the experimental results. The underlying theory behind the elicitation process is being presented and subsequently an aero-engine Fan Blade Off (FBO) case study is presented. The framework is used to illustrate the way in which expert judgements are implemented as inputs into the MATLAB model which is used to predict different parameters of interest associated to FBO events such as probabilities of having a particular speed during an event as well as what are the characteristics of the most likely events to occur. Those are taken into consideration in order to allow the designer to perform relevant and more detailed analysis on the fan subsystem during the preliminary design process

A probabilistic multi-fidelity aero-engine preliminary design optimization framework: technical and commercial perspectives

Conceptual and preliminary design phases of aerospace gas turbines compromise a particularly uncertain and challenging stage of their development. It is at these early design phases when the most critical and influential architectural decisions are made. The outcomes of those decisions have a direct impact on a multitude of the aero-engine design attributes such as performance, weight, specific fuel consumption and life-cycle cost - the factors directly influencing the economic value and market success of a prospective power system. Hence, the commercial success of a specific aero-engine and the technical aspects of the processes used in its design are strongly correlated. This work targets the examination of that relationship and presents a rationale for the development of an IntegratedFramework for Uncertainty Quantification and Multi-Objective Optimization. First, the commercial aspects of a typical aerospace design project are considered. Then, the top level structure of aero-engine design process is considered from the technical point of view. Finally, the top-level architecture of the framework is discussed and a brief update on the current development status of its implementation is presented

An integrated framework for Bayesian uncertainty quantification and probabilistic multi-criteria decision making in aero-engine preliminary design

The following paper presents a novel framework that enables making early design decisions based on probabilistic information obtained from fast, deterministic, low-fidelity tools, calibrated against high-fidelity data that is supported by experts’ knowledge. The proposed framework integrates a Probabilistic Multi-Criteria Decision Making technique with Bayesian Uncertainty Quantification concepts supported by the Kennedy and O’Hagan Framework. It allows continuous improvement of low-fidelity design tools as high-fidelity data is gathered and therefore facilitates investigation into the impacts the accumulation of high-fidelity data has on preliminary design process risk. The paper discusses theoretical concepts behind the framework and demonstrates its relevance by application in an illustrative combustor preliminary design case study