Noise-robust stress intensity factor determination from kinematic field measurements

Stress intensity factors are often estimated numerically from a given displacement field through an interaction integral formalism. The latter method makes use of a weight, the virtual crack extension field, which is under-constrained by first principles. Requiring a least noise sensitivity allows one to compute the optimal virtual crack extension. Mode I and mode II specialized fields are obtained and particularized for a given displacement functional basis. The method is applied to an experimental case study of a crack in a silicon carbide sample, whose displacement field is obtained by a digital image correlation technique. The optimization leads to a very significant uncertainty reduction up to a factor 100 of the non-optimized formulation. The proposed scheme reveals additional performances with respect to the integral domain choice and assumed crack tip geometry, which are shown to have a reduced influence.     

Design of a sampling strategy to optimally calibrate a reactive transport model: Exploring the potential for Escherichia coli in the Scheldt Estuary

For the calibration of any model, measurements are necessary. As measurements are expensive, it is of interest to determine beforehand which kind of samples will provide maximal information. Using a criterion related to the Fisher information matrix as a measure for information content, it is possible to design a sampling scheme that will enable the most precise parameter estimates. This approach was applied to a reactive transport model (based on the Second-generation Louvain-la-Neuve Ice-ocean Model, SLIM) of Escherichia coli concentrations in the Scheldt Estuary. As this estuary is highly influenced by the tide, it is expected that careful timing of the samples with respect to the tidal cycle can have an effect on the quality of the data. The timing and also the positioning of samples were optimised according to the proposed criterion. In the investigated case studies the precision of the estimated parameters could be improved by up to a factor of ten, confirming the usefulness of this approach to maximize the amount of information that can be retrieved from a fixed number of samples. Precise parameter values will result in more reliable model simulations, which can be used for interpretation, or can in turn serve to plan subsequent sampling campaigns to further constrain the model parameters.     

Constructive solution of a bilinear optimal control problem for a Schrödinger equation

Often considered in numerical simulations related to the control of quantum systems, the so-called monotonic schemes have not been so far much studied from the functional analysis point of view. Yet, these procedures provide an efficient constructive method for solving a certain class of optimal control problems. This paper aims both at extending the results already available about these algorithms in the finite-dimensional case (i.e., the time-discretized case) and at completing those of the continuous case. This paper starts with some results about the regularity of a functional related to a wide class of models in quantum chemistry. These enable us to extend an inequality due to Łojasiewicz to the infinite-dimensional case. Finally, some inequalities proving the Cauchy character of the monotonic sequence are obtained, followed by an estimation of the rate of convergence.     

A functional formalization of on chip communications

This paper presents a formal model and a systematic approach to the validation of communication architectures at a high level of abstraction. This model is described mathematically by a function, named GeNoC. The correctness of GeNoC is expressed as a theorem, which states that messages emitted on the architecture reach their expected destination without any modification of their content. The model identifies the key constituents common to all on chip communication architectures, and their essential properties from which the correctness theorem is deduced. Each constituent is represented by a function that has no explicit definition but is constrained to satisfy the essential properties. Thus, the validation of a particular architecture is reduced to the proof that its concrete definition satisfies the essential properties. In practice, the model has been defined in the logic of the ACL2 theorem proving system. We illustrate our approach on several architectures that constitute concrete instances of the generic GeNoC model. Some of these applications come from industrial designs, such as the AMBA AHB bus or the Octagon network from ST Microelectronics. C. Delgado Kloos     

Smaller is stronger: The effect of strain hardening

Single-crystal face-centered cubic metal pillars synthesized using a focused ion beam are reported to be stronger when compressed in smaller volumes. Using in situ Laue diffraction and crystal plasticity simulations it is shown that plastic deformation is initially controlled by the boundary constraints of the microcompression tests, followed by classical crystal plasticity for uniaxial compression. Taking the stress at which the change between the two modes occurs as strength of the pillar instead of the flow stress at a fixed amount of strain, the “smaller is stronger” trend is considerably reduced, if not eliminated, and what remains is a size dependence in strain hardening. The size-dependent increase in flow stress is a result of the early activation of multiple slip systems and thus the evolution of the microstructure during compression.     

EEG-based synchronized brain-computer interfaces: a model for optimizing the number of mental tasks.

The information-transfer rate (ITR) is commonly used to assess the performance of brain-computer interfaces (BCIs). Various studies have shown that the optimal number of mental tasks to be used is fairly low, around 3 or 4. We propose an experimental validation as well as a formal approach to demonstrate and confirm that this optimum is user and BCI design dependent. Even if increasing the number of mental tasks to the optimum indeed leads to an increase of the ITR, the gain remains small. This might not justify the added complexity in terms of protocol design.     

Least Economic Cost Regional Water Supply Planning – Optimising Infrastructure Investments and Demand Management for South East England’s 17.6 Million People

This paper presents a deterministic capacity expansion optimisation model designed for large regional or national water supply systems. The annual model selects, sizes and schedules new options to meet predicted demands at minimum cost over a multi-year time horizon. Options include: supply-side schemes, demand management (water conservation) measures and bulk transfers. The problem is formulated as a mixed integer linear programming (MILP) optimisation model. Capital, operating, carbon, social and environmental costs of proposed discrete schemes are considered. User-defined annual water saving profiles for demand management schemes are allowed. Multiple water demand scenarios are considered simultaneously to ensure the supply–demand balance is preserved across high demand conditions and that variable costs are accurately assessed. A wide range of supplementary constraints are formulated to consider the interdependencies between schemes (pre-requisite, mutual exclusivity, etc.). A two-step optimisation scheme is introduced to prevent the infeasibilities that inevitably appear in real applications. The model was developed for and used by the ‘Water Resources in the South East’ stakeholder group to select which of the 316 available supply schemes (including imports) and 511 demand management options (considering 272 interdependencies) are to be activated to serve the inhabitants of South East of England. Selected schemes are scheduled and sized over a 25 year planning horizon. The model shows demand management options can play a significant role in the region’s water supply and should be considered alongside new supplies and regional transfers. Considering demand management schemes reduced overall total discounted economic costs by 10 % and removed two large reservoirs from the least-cost plan. This case-study optimisation model was built using a generalised data management software platform and solved using a mixed integer linear programme.