Materials Map

Discover the materials research landscape. Find experts, partners, networks.

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

×

Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Achintha, Mithila

  • Google
  • 17
  • 30
  • 234

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (17/17 displayed)

  • 2024Glass–GFRP Laminate: A Proof of Concept Experimental Investigation2citations
  • 2023Exploration of Waste Glass Powder as Partial Replacement of Cement in Concrete2citations
  • 2022Glass–GFRP Sandwich: Structurally Superior Laminated Glasscitations
  • 2020Development of cohesive zone models for the prediction of damage and failure of glass/steel adhesive joints41citations
  • 2019Failure prediction and optimal selection of adhesives for glass/steel adhesive joints20citations
  • 2018Strength evaluation and failure prediction of bolted and adhesive glass/steel joints20citations
  • 2016A review on design, manufacture and mechanics of composite risers64citations
  • 2015An CFRP fabrics as internal reinforcement in concrete beamscitations
  • 2015An experimentally validated contour method/eigenstrains hybrid model to incorporate residual stresses in glass structural designs13citations
  • 2015Experimental and numerical investigation of residual stress relaxation in shot-peened notch geometries under low-cycle fatiguecitations
  • 2014Fatigue behaviour of geometric features subjected to laser shock peening72citations
  • 2014Hybrid contour method/eigenstrain model for predicting residual stress in glasscitations
  • 2012Fatigue behaviour of geometric features subjected to laser shock peeningcitations
  • 2012Fatigue behaviour of geometric features subjected to laser shock peening:9th Fatigue Damage of Structural Materials Conferencecitations
  • 2012Prediction of FRP debonding Using the global-energy-balance approachcitations
  • 2011Optimising LSP conditions and modelling the geometric effects on residual stresscitations
  • 2009Fracture mechanics of plate debondingcitations

Places of action

Chart of shared publication
Yildirim, Feyza
2 / 2 shared
Wang, Yong
1 / 21 shared
Chand, Gaurav
1 / 4 shared
Thomsen, Ole
2 / 16 shared
Feih, Stefanie
3 / 4 shared
Katsivalis, Ioannis
3 / 14 shared
Thomsen, Ole Thybo
1 / 60 shared
Pham, Dinh-Chi
1 / 1 shared
Sridhar, N.
1 / 4 shared
Qian, Xudong
1 / 1 shared
Shenoi, Ajit
1 / 2 shared
Sobey, Adam
1 / 9 shared
Bloodworth, A. G.
1 / 3 shared
Alami, F.
1 / 1 shared
Balan, B.
2 / 3 shared
You, Chao
1 / 4 shared
Reed, Philippa
1 / 9 shared
Soady, K. A.
1 / 6 shared
Sackett, E.
1 / 4 shared
Fufari, D.
1 / 3 shared
Nowell, D.
1 / 10 shared
Bache, M.
1 / 4 shared
Sackett, Liz
2 / 2 shared
Nowell, David
3 / 3 shared
Bache, Martin
2 / 5 shared
Furfari, Domenico
2 / 4 shared
Guan, G.
1 / 1 shared
Burgoyne, C.
2 / 4 shared
Withers, Phillip
1 / 1 shared
Shapiro, Karen
1 / 1 shared
Chart of publication period
2024
2023
2022
2020
2019
2018
2016
2015
2014
2012
2011
2009

Co-Authors (by relevance)

  • Yildirim, Feyza
  • Wang, Yong
  • Chand, Gaurav
  • Thomsen, Ole
  • Feih, Stefanie
  • Katsivalis, Ioannis
  • Thomsen, Ole Thybo
  • Pham, Dinh-Chi
  • Sridhar, N.
  • Qian, Xudong
  • Shenoi, Ajit
  • Sobey, Adam
  • Bloodworth, A. G.
  • Alami, F.
  • Balan, B.
  • You, Chao
  • Reed, Philippa
  • Soady, K. A.
  • Sackett, E.
  • Fufari, D.
  • Nowell, D.
  • Bache, M.
  • Sackett, Liz
  • Nowell, David
  • Bache, Martin
  • Furfari, Domenico
  • Guan, G.
  • Burgoyne, C.
  • Withers, Phillip
  • Shapiro, Karen
OrganizationsLocationPeople

document

Optimising LSP conditions and modelling the geometric effects on residual stress

  • Withers, Phillip
  • Nowell, David
  • Shapiro, Karen
  • Achintha, Mithila
Abstract

compressive stresses close to the surface of a metal component. The method is particularly useful in the surface treatments of highly-stressed alloys used in the aerospace industry. LSP typically produces compressive zones over 1.5-2.0mm deep, in comparison to about 0.25mm produced by conventional shot peening. The laser parameters can be relatively easily controlled, allowing the process to be tailored to specific design requirements. Additionally, the flexibility of the process allows peening of complex geometries (e.g. leading edges of aero-engine blades). However, a comprehensive analytical or numerical method for predicting the residual stress (RS) distributions generated by LSP is lacking. Consequently, the method is not being exploited as effectively as it might be and in some situations (e.g. in complex geometries) the process has failed to give the expected benefits.The current study forms part of a wider programme of work involving a number of industrial and academic collaborators and the study developed a comprehensive understanding of the LSP process through interpretation of experimental and model results. The experimental work involves measuring and understanding how laser process parameters, specimen geometry and material properties affect the RS fields caused by LSP. X-ray and neutron diffraction techniques have been used to measure RS profiles in Ti-6Al-4V and aluminium alloys (Al2024 and Al7050), all of which are widely used in the aerospace industry for a range of LSP parameters. The experimental results are used to determine the optimal peening conditions and also to quantify the fatigue performance of specimens with a wide range of geometries.A more physically-based eigenstrain (i.e. misfit strain) model which considered the plastic strains introduced by the process has been developed to determine the RS field generated by LSP [1]. Due to propagation of the shock wave generated by a laser shock, the top layers of the specimen experience plastic deformation, and on relaxation the deformed material is loaded in compression by the undeformed material which surrounds this region. Thus, the plastic deformation caused by the shock wave generates the RS field, and also once the plastic deformations are fully stabilised the response of the workpiece is elastic. In the present model, the effect of the LSP pulse is first modelled as a dynamic pressure load in an explicit FE model in order to determine the stabilised plastic strain distribution, which is then incorporated into a static FE model as an eigenstrain. The elastic response of the static FE model gives the RS distribution generated by the original laser pulse.The eigenstrain analysis has a number of advantages. Firstly, once the eigenstrains have been determined, thecomplete RS distribution can be reconstructed through a single elastic analysis, and hence, the solution can bedetermined at a manageable computational cost. The formulation of the solution this way ensures strain compatibility, global stress equilibrium, and matches the boundary conditions. The results have shown that the LSP process parameters can be directly linked to the underlying eigenstrain distribution, and also, a given laser setting produces similar eigenstrain distributions in workpieces (of a given material) of different geometries. Therefore, it is possible to undertake a rapid assessment of the RS field caused in new or complex geometries, and also, the effect of multiple LSP shots simply by installing the appropriate eigenstrain distributions at the correct locations within the component.

Topics
  • impedance spectroscopy
  • surface
  • polymer
  • aluminium
  • fatigue
  • aluminium alloy
  • neutron diffraction