Ductile tearing of 2024 aluminum alloy panels

International audienceTwo 2024 aluminum alloys are studied. Their second phase volume fraction differ as well as their mean inter-particle ....

Nonlocal computational methods applied to composites structures

International audienceA nonlocal finite element method is used to solve numerical problems appearing when a standard finite element method, coupled with a Newton-Raphson algorithm, is used to model the degradation of organic or ceramic matrix composites structures (OMC or CMC) even under simple solicitations (traction, flexion, ...). The main problem is related to instabilities and localisation, which lead to the divergence of the solver. In order to overcome these difficulties, a new method is developed. It consists in the use of nonlocal description of the material combined with an arc length algorithm. This ensures a good numerical conditioning which allows the parallelization (using a FETI method) of the calculations and therefore high performance computations.This set of tools allows to run 3D simulations in order to follow the initiation and the propagation of fracture in cases representative of industrial problems which require very fine meshes

A bias-compensated MUSIC for small number of samples

The multiple signal classification (MUSIC) method is known to be asymptotically efficient, yet with a small number of snapshots its performance degrades due to bias in MUSIC localization function. In this communication, starting from G-MUSIC which improves over MUSIC in low sample support, a high signal to noise ratio approximation of the G-MUSIC localization function is derived. This approximation results in closed-form expressions of the weights applied to each eigenvector of the sample covariance matrix. A new method which consists in minimizing this simplified G-MUSIC localization function is thus in- troduced, and referred to as sG-MUSIC. Interestingly enough, this sG-MUSIC criterion can be interpreted as a bias correction of the conventional MUSIC localization function. Numerical simulations indicate that sG-MUSIC incur only a marginal loss in terms of mean square error of the direction of arrival estimates, as compared to G-MUSIC, and performs better than MUSI

On using an inexact floating-point LP solver for deciding linear arithmetic in an SMT solver

International audienceOff-the-shelf linear programming (LP) solvers trade soundness for speed: for efficiency, the arithmetic is not exact rational arithmetic but floating-point arithmetic. As a side-effect the results come without any formal guarantee and cannot be directly used for decid- ing linear arithmetic. In this work we explain how to design a sound procedure for linear arithmetic built upon an inexact floating-point LP solver. Our approach relies on linear programming duality to instruct a black-box off-the-shelf LP solver to output, when the problem is not satisfiable, an untrusted proof certificate. We present a heuristic post- processing of the certificate which accommodates for certain numeric inaccuracies. Upon success it returns a provably correct proof witness that can be independently checked. Our preliminary results are promising. For a benchmark suite extracted from SMT verification problems the floating-point LP solver returns a result for which proof witnesses are successfully and efficiently generated

Novel ligature methods for studying sublethal effects of sit-and-wait predators: test using Cordulegaster boltonii (Donovan, 1807) larvae (Anisoptera: Cordulegasteridae)

A novel method of labial palp ligature was tested as a substitute for palp ablation for studying sublethal effects of larvae of C. boltonii on prey populations and their consequences for ecosystem functioning. Two alternative types of ligature were designed to test for neutral or aggressive, but non-lethal, predator-prey interaction effects. Ligature efficiency in preventing prey capture was very high and the effects on larval survival and emergence success were negligible. Potential advantages and drawbacks, compared to other methods, are discussed. The results indicate that this fully reversible method should be applied whenever possible, especially for naturally rare or endangered odon. spp

Computing stack maps with interfaces

International audienceLightweight bytecode verification uses stack maps to annotate Java bytecode programs with type information in order to reduce the verification to type checking. This paper describes an improved bytecode analyser together with algorithms for optimizing the stack maps generated. The analyser is simplified in its treatment of base values (keeping only the necessary information to ensure memory safety) and enriched in its representation of interface types, using the Dedekind-MacNeille completion technique. The computed interface information allows to remove the dynamic checks at interface method invocations. We prove the memory safety property guaranteed by the bytecode verifier using an operational semantics whose distinguishing feature is the use of un-tagged 32-bit values. For bytecode typable without sets of types we show how to prune the fix-point to obtain a stack map that can be checked without computing with sets of interfaces i.e., lightweight verification is not made more complex or costly. Experiments on three substantial test suites show that stack maps can be computed and correctly pruned by an optimized (but incomplete) pruning algorithm

Hybrid Monitoring of Attacker Knowledge

International audienceEnforcement of noninterference requires proving that an attacker's knowledge about the initial state remains the same after observing a program's public output. We propose a hybrid monitoring mechanism which dynamically evaluates the knowledge that is contained in program variables. To get a precise estimate of the knowledge, the monitor statically analyses non-executed branches. We show that our knowledge-based monitor can be combined with existing dynamic monitors for non-interference. A distinguishing feature of such a combination is that the combined monitor is provably more permissive than each mechanism taken separately. We demonstrate this by proposing a knowledge-enhanced version of a no-sensitive-upgrade (NSU) monitor. The monitor and its static analysis have been formalized and proved correct within the Coq proof assistant

Using JavaScript Monitoring to Prevent Device Fingerprinting

Today’s Web users are continuously tracked as they browse the Web. One of the techniques for tracking is device fingerprinting that distinguishes users based on their Web browser and operating system properties. We propose solutions to detect and prevent device fingerprinting via runtime monitoring of JavaScript programs

A Verified CompCert Front-End for a Memory Model Supporting Pointer Arithmetic and Uninitialised Data

International audienceThe CompCert C compiler guarantees that the target program behaves as the source program. Yet, source programs without a defined semantics do not benefit from this guarantee and could therefore be miscompiled. To reduce the possibility of a miscompilation, we propose a novel memory model for CompCert which gives a defined semantics to challenging features such as bitwise pointer arithmetics and access to uninitialised data. We evaluate our memory model both theoretically and experimentally. In our experiments, we identify pervasive low-level C idioms that require the additional expressiveness provided by our memory model. We also show that our memory model provably subsumes the existing CompCert memory model thus cross-validating both semantics. Our memory model relies on the core concepts of symbolic value and normalisa-tion. A symbolic value models a delayed computation and the normalisation turns, when possible, a symbolic value into a genuine value. We show how to tame the expressive power of the normalisation so that the memory model fits the proof framework of CompCert. We also adapt the proofs of correctness of the compiler passes performed by CompCert's front-end, thus demonstrating that our model is well-suited for proving compiler transformations

Combining Individual Phenotypes of Feed Intake With Genomic Data to Improve Feed Efficiency in Sea Bass

Measuring individual feed intake of fish in farms is complex and precludes selective breeding for feed conversion ratio (FCR). Here, we estimated the individual FCR of 588 sea bass using individual rearing under restricted feeding. These fish were also phenotyped for their weight loss at fasting and muscle fat content that were possibly linked to FCR. The 588 fish were derived from a full factorial mating between parental lines divergently selected for high (F+) or low (F–) weight loss at fasting. The pedigree was known back to the great grand-parents. A subset of 400 offspring and their ancestors were genotyped for 1,110 SNPs which allowed to calculate the genomic heritability of traits. Individual FCR and growth rate in aquarium were both heritable (genomic h2 = 0.47 and 0.76, respectively) and strongly genetically correlated (−0.98) meaning that, under restricted feeding, faster growing fish were more efficient. FCR and growth rate in aquariums were also significantly better for fish with both parents from F– (1.38), worse for fish with two parents F+ (1.51) and intermediate for cross breed fish (F+/F– or F–/F+ at 1.46). Muscle fat content was positively genetically correlated to growth rate in aquarium and during fasting. Thus, selecting for higher growth rate in aquarium, lower weight loss during fasting and fatter fish could improve FCR in aquarium. Improving these traits would also improve FCR of fish in normal group rearing conditions, as we showed experimentally that groups composed of fish with good individual FCR were significantly more efficient. The FCR of groups was also better when the fish composing the groups had, on average, lower estimated breeding values for growth rate during fasting (losing less weight). Thus, improving FCR in aquarium and weight loss during fasting is promising to improve FCR of fish in groups but a selection response experiment needs to be done. Finally, we showed that the reliability of estimated breeding values was higher (from+10% up to +125%) with a genomic-based BLUP model than with a traditional pedigree-based BLUP, showing that genomic data would enhance the accuracy of the prediction of EBV of selection candidates