Modelling of Strengthening of Al-Li-Cu-Mg alloys

Starink, M.J.; Hobson, A; Gregson, P.J.

doi:10.4028/www.scientific.net/msf.331-337.1321

Cited by 5 publications

(7 citation statements)

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“…Figure 51 compares the cross sections for the calulations of Ref. [241,243] with the experimental data, as a function of the missing momentum at the three values of ω [244]. For this calculation final state interactions for the outgoing protons were taken into account by using distorted waves but neglecting their mutual interaction.…”

Section: Results For Thementioning

confidence: 99%

“…Calculation for the 16 O(e, e ′ pp) case have shown that the transition to the ground state of 14 C is dominated by the high-momentum components in the two-nucleon overlap function. Comparison with the data from NIKHEF for this reaction have provided a clear signature of SRC effects [237,244]. An important ingredient in the description of two-nucleon knockout reactions is the two-hole spectral function.…”

Section: Results For Thementioning

confidence: 99%

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Self-consistent Green's function method for nuclei and nuclear matter

Dickhoff

Barbieri

2004

Progress in Particle and Nuclear Physics

494

599

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Recent results obtained by applying the method of self-consistent Green's functions to nuclei and nuclear matter are reviewed. Particular attention is given to the description of experimental data obtained from the (e,e ′ p) and (e,e ′ 2N) reactions that determine one and two-nucleon removal probabilities in nuclei since the corresponding amplitudes are directly related to the imaginary parts of the single-particle and two-particle propagators. For this reason and the fact that these amplitudes can now be calculated with the inclusion of all the relevant physical processes, it is useful to explore the efficacy of the method of self-consistent Green's functions in describing these experimental data. Results for both finite nuclei and nuclear matter are discussed with particular emphasis on clarifying the role of short-range correlations in determining various experimental quantities. The important role of long-range correlations in determining the structure of lowenergy correlations is also documented. For a complete understanding of nuclear phenomena it is therefore essential to include both types of physical correlations. We demonstrate that recent experimental results for these reactions combined with the reported theoretical calculations yield a very clear understanding of the properties of all protons in the nucleus. We propose that this knowledge of the properties of constituent fermions in a correlated many-body system is a unique feature of nuclear physics.

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Section: Results For Thementioning

confidence: 99%

Section: Results For Thementioning

confidence: 99%

Self-consistent Green's function method for nuclei and nuclear matter

Dickhoff

Barbieri

2004

Progress in Particle and Nuclear Physics

494

599

View full text Add to dashboard Cite

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“…Hence, there exists a considerable body of work on modelling independent contributions of strength in alloys and composites but predictive modelling of properties of complex alloys and composites requires superposition of these contributions. This type of complex strength modelling has been performed, to a varying degree of detail, for several monolithic precipitation hardened alloys [3,4,5,25,52,54,55], and recently a detailed model of strengthening in precipitation hardened metal matrix composites (MMCs) has been reported by the present authors [56,57,58]. In the strength modelling approach adopted in the present paper, the strengthening of MMCs and monolithic alloys are ascribed to five mechanisms: i. Precipitation strengthening, which involves strengthening of grains due to GPB zones, δ' (Al 3 Li) phase and S′ (Al 2 CuMg) phase [59,60], with a small contribution due to β′ (Al 3 Zr) dispersoids.…”

Section: Physically-based Modellingmentioning

confidence: 99%

“…This indicates that the elements of the physically-based model presented are sound and that, in general, strength modelling of complex alloys can be successfully pursued using a physicallybased approach. It must however be emphasised that the amount of data for the NF and SVM model training was clearly well below that which may be expected to reasonably represent a problem of this complexity and the physically-based model required extensive experimental [58,59,60] and analytical [56,57] [59] and the physically based model.…”

Section: Physically-based Modellingmentioning

confidence: 99%

Predicting the Structural Performance of Heat-Treatable Al-Alloys

Starink

Sinclair

Reed

et al. 2000

MSF

Self Cite

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Advances in physically-based and adaptive numeric modelling (ANM) have lead to a significant elevation of the role of modelling in commercial alloy development and process optimisation. Within these two categories of modelling a wide variety of techniques exists, whilst hybrid approaches, taking advantage of the benefits of the both methods, are also being developed. In this paper various ANM techniques and physically-based models relevant for modelling and predicting the properties of heat treatable Al-based alloys are reviewed, and case studies involving the modelling of proof stress, toughness and conductivity of a range of Al-based alloys are presented. These case studies illustrate that successful modelling requires an in-depth understanding of the various modelling options. Selection of the optimum modelling approach is driven by a range of factors, such as size of database available (large databases are best analysed using adaptive numeric modelling approaches), and availability of sound physical understanding (the latter benefiting physically-based approaches). 1.Introduction Throughout the history of alloy development, the modelling of properties and microstructure-property relationships has lagged behind the commercialisation of new products and processes. In terms of agehardened Al-alloys, commercial aerospace applications were established by 1919, however the first basic models of age hardening, based on dislocation movement and dislocation pinning, were not developed until the 1940's [1,2], whilst the first detailed models of strengthening in multi-component Al-based alloys were only published in the 1980/90s [3,4,5]. In recent years, this time lag has been reduced, with modelling preceding or directly leading product development in some cases. A specific example is the formulation of new compositions of Ni-based superalloys by Rolls-Royce Plc. which are based on thermodynamic modelling, and the recent development of 7449 and 7040 Al-alloy plate which has been influenced by microstructure-property modelling [6]. The use of well-founded modelling approaches has clear advantages in directing product development in a cost effective manner.Whilst the above examples concern modelling through physical understanding of microstructures and microstructure development, modelling using adaptive numeric (AN) approaches such as artificial neural networks has recently made important advances. Current state-of-the-art adaptive numeric modelling combines flexible, adaptive algorithms for model construction with a rigorous mathematical/statistical basis [7,8].The purpose of the present paper is to highlight recent advances in physically-based and AN modelling, and to consider the relative benefits of the two approaches as well as hybrid approaches which use elements of both. In exploring this wide ranging and continuous field of modelling approaches we will start by introducing some of the better known techniques. On one side of the spectrum of modelling

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“…A method has been developed for obtaining the volume fractions of the precipitates based on the heat evolutions due to precipitation of the phases as measured by DSC. 4,29,30,31,32 Assuming that a precipitate of composition M m A a B b C c is formed, the heat effect measured in DSC is then given by:…”

Section: Applications For Light Alloysmentioning

confidence: 99%

Using differential scanning calorimetry as an analytical tool for ultrafine grained metals processed by severe plastic deformation

Gao

Starink

Langdon

2009

Materials Science and Technology

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Differential Scanning Calorimetry (DSC) is a thermal analysis technique that measures the energy absorbed or released by a sample as a function of temperature or time. Analysis by DSC has wide applications for examining solid-state reactions and solid-liquid reactions in many different materials. Quantitative analyses of the kinetics of reactions may be assessed by reviewing the interrelation between activation energy analysis methods. In recent years, DSC has been applied in the examination and analysis of bulk ultrafine-grained materials processed through the application of Severe Plastic Deformation (SPD). This overview examines these recent reports with reference to materials processed using the procedures of Equal-Channel Angular Pressing (ECAP), High-Pressure Torsion (HPT) and Accumulative Roll-Bonding (ARB). In addition, some critical issues related to DSC analysis are also discussed.

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Modelling of Strengthening of Al-Li-Cu-Mg alloys

Cited by 5 publications

References 0 publications

Self-consistent Green's function method for nuclei and nuclear matter

Self-consistent Green's function method for nuclei and nuclear matter

Predicting the Structural Performance of Heat-Treatable Al-Alloys

Using differential scanning calorimetry as an analytical tool for ultrafine grained metals processed by severe plastic deformation

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