On the control of the load increments for a proper description of multiple delamination in a domain decomposition framework

In quasi-static nonlinear time-dependent analysis, the choice of the time discretization is a complex issue. The most basic strategy consists in determining a value of the load increment that ensures the convergence of the solution with respect to time on the base of preliminary simulations. In more advanced applications, the load increments can be controlled for instance by prescribing the number of iterations of the nonlinear resolution procedure, or by using an arc-length algorithm. These techniques usually introduce a parameter whose correct value is not easy to obtain. In this paper, an alternative procedure is proposed. It is based on the continuous control of the residual of the reference problem over time, whose measure is easy to interpret. This idea is applied in the framework of a multiscale domain decomposition strategy in order to perform 3D delamination analysis

Bridging Proper Orthogonal Decomposition methods and augmented Newton-Krylov algorithms: an adaptive model order reduction for highly nonlinear mechanical problems

This article describes a bridge between POD-based model order reduction techniques and the classical Newton/Krylov solvers. This bridge is used to derive an efficient algorithm to correct, "on-the-fly", the reduced order modelling of highly nonlinear problems undergoing strong topological changes. Damage initiation problems are addressed and tackle via a corrected hyperreduction method. It is shown that the relevancy of reduced order model can be significantly improved with reasonable additional costs when using this algorithm, even when strong topological changes are involved

Increased Production of the Soluble Tumor-Associated Antigens CA19-9, CA125, and CA15-3 in Rheumatoid Arthritis

Some tumor-associated antigens (TAAs) are expressed on inflammatory cells. We previously detected carcinoembryonic antigen (CEA; CD66) in the rheumatoid (RA) synovium. The production of CEA, CA19-9, CA125, and CA15.3, may be increased in patients with RA, scleroderma, lupus, and SjÖgren's syndrome (SS). Some of these TAAs contain sialylated carbohydrate motifs and they are involved in tumor-associated cell adhesion and metastasis. We assessed levels of TAAs in the sera of RA patients and healthy subjects. Serum TAA levels were correlated with disease markers including serum rheumatoid factor (RF), C-reactive protein (CRP), and anti-CCP antibody levels, DAS28, age disease duration. TAAs including CEA, CA15-3, CA72-4, CA125, and CA19-9, and neuron-specific enolase (NSE) were assessed by immunoassay in the sera of 75 patients with RA and 50 age- and sex-matched healthy controls. Normal upper limits for these TAAs were 3.4 Μg/L, 25 kU/L, 6.9 kU/L, 35 kU/L, 34 kU/L, and 16.3 Μg/L, respectively. There were significantly more RA patients showing abnormally high levels of CA125 (10.8% versus 7.1%), CA19-9 (8.1% versus 0%), and CA15-3 (17.6% versus 14.3%) in comparison to controls ( P < 0.05). The mean absolute serum levels of CA125 (23.9 ± 1.8 versus 16.8 ± 2.2 kU/L) and CA19-9 (14.2 ± 1.2 versus 10.5 ± 1.6 kU/L) were also significantly higher in RA compared to controls ( P < 0.05). Among RA patients, serum CEA showed significant correlation with RF ( r = 0.270; P < 0.05). None of the assessed TAAs showed any correlation with CRP, anti-CCP, DAS28, age or disease duration. The concentration of some TAAs may be elevated in the sera of patients with established RA in comparison to healthy subjects. CEA, CA19-9, CA125, and CA15-3 contain carbohydrate motifs and thus they may be involved in synovitis-associated adhesive events. Furthermore, some TAAs, such as CEA, may also correlate with prognostic factors, such as serum RF levels.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73224/1/annals.1422.037.pd

A three-scale domain decomposition method for the 3D analysis of debonding in laminates

The prediction of the quasi-static response of industrial laminate structures requires to use fine descriptions of the material, especially when debonding is involved. Even when modeled at the mesoscale, the computation of these structures results in very large numerical problems. In this paper, the exact mesoscale solution is sought using parallel iterative solvers. The LaTIn-based mixed domain decomposition method makes it very easy to handle the complex description of the structure; moreover the provided multiscale features enable us to deal with numerical difficulties at their natural scale; we present the various enhancements we developed to ensure the scalability of the method. An extension of the method designed to handle instabilities is also presented