LTV stochastic systems stabilization with large and variable input delay

In this paper we propose a solution to the state-feedback and output-feedback stabilization problem for linear time-varying stochastic systems affected by arbitrarily large and variable input delay. It is proved that under the proposed controller the underlying stochastic process is exponentially centered and mean square bounded. The solution is given through a set of delay differential equations with cardinality proportional to the delay bound. The predictor is based on the semigroup generated by the closed-loop system in absence of delay, and its computation is described by a numerically reliable and robust method. In the deterministic case this method generates the same optimal trajectories as in the delay-less case

Projecting seismicity induced by complex alterations of underground stresses with applications to geothermal systems

Seismicity associated with subsurface operations is a major societal concern. It is therefore critical to improve predictions of the induced seismic hazard. Current statistical approaches account for the physics of pore pressure increase only. Here, we present a novel mathematical model that generalises adopted statistics for use in arbitrary injection/production protocols and applies to arbitrary physical processes. In our model, seismicity is driven by a normalised integral over the spatial reservoir volume of induced variations in frictional Coulomb stress, which—combined with the seismogenic index—provides a dimensionless proxy of the induced seismic hazard. Our model incorporates the classical pressure diffusion based and poroelastic seismogenic index models as special cases. Applying our approach to modeling geothermal systems, we find that seismicity rates are sensitive to imposed fluid-pressure rates, temperature variations, and tectonic conditions. We further demonstrate that a controlled injection protocol can decrease the induced seismic risk and that thermo-poroelastic stress transfer results in a larger spatial seismic footprint and in higher-magnitude events than does direct pore pressure impact for the same amount of injected volume and hydraulic energy. Our results, validated against field observations, showcase the relevance of the novel approach to forecast seismic hazards induced by subsurface activities

Influence of production batch related parameters on static and fatigue resistance of LPBF produced AlSi7Mg0.6

In laser powder bed fusion (LPBF), the influence material properties are often determined as a function of the inclination with respect to the build direction. In industrial production with variable component shapes and dimensions, the part orientation will often be a matter of the available space in the build volume. Additionally, build-to-build variability is an important factor that may impact the mechanical properties that are often not quantified. Such sources of variability are of great importance for highly demanding sectors such as aviation and aerospace, where lightweight Al-alloys are often used with the geometrical freedom given by the LPBF process. Hence, this work systematically investigates the influence of production batch-related parameters together with part inclination in the LPBF of AlSi7Mg0.6 alloy. Three builds were executed to quantify the impact of the batch, part position, and inclination on the static and fatigue resistance of the alloy in a completely randomized experimental design using an industrial LPBF machine. The results were analysed by the appropriate statistical methods both for discrete and functional data. The results showed that while the part orientation only influenced the static properties, the part position significantly affected the fatigue life demonstrated by the different low cycle fatigue life coefficients

Filtering Discrete-Time Systems With Multiplicative Noise in L-2 Spaces With Applications

In this work we adopt a novel formulation of the distributed parameters recursive filter for discrete-time systems evolving in L-2 spaces to widen the class of systems that can be processed by a state estimation algorithm. Starting from a rigorous definition of Kronecker algebra on L-2 spaces that involves both elements and bounded operators of L-2, we provide a computationally efficient solution in the case of linear systems with multiplicative noises. We illustrate the potential application of the approach by developing a case-study concerning the conceptual design of a distributed thermo-couple in the presence of the Nyquist-Johnson noise

LQ non-Gaussian Control with I/O packet losses

The paper concerns the Linear Quadratic non-Gaussian (LQnG) sub-optimal control problem when the input and output signals travel through an unreliable network, namely Gilbert-Elliot channels. In particular, the input/output packet losses are modeled by Bernoulli sequences, and we assume that the moments of the non-Gaussian noises up to the fourth order are known. By mean of a suitable rewriting of the system through an intermittent output injection term, and by considering an augmented system with the second-order Kronecker power of the measurements, a simple solution is provided by substituting the Kalman predictor with intermittent observations of the LQG control law with a quadratic optimal predictor. Numerical simulations show the effectiveness of the proposed method

Nematic liquid crystal reorientation around multi-walled carbon nanotubes mapped via Raman microscopy

We have studied the formation of topological defects in liquid crystal (LC) matrices induced by multiwalled carbon nanotubes (MWCNTs) and external electric fields. The defects are ascribable to a distortion of the LC molecular director in proximity of the MWCNT surface. The system is analyzed macroscopically using spectroscopic variable angle ellipsometry. Concurrently, confocal micro-Raman spectroscopy is used to study the system state at the microscale. This allows to acquire a three-dimensional, spatially-resolved map of the topological defect, determining scale length variations and orientation topography of the LC molecules around the MWCNT

Potential of native and bioprocessed brewers' spent grains as organic soil amendments

Introduction: The use of novel soil amendments and the exploitation of plant growth-promoting microorganisms are considered promising tools for developing a more sustainable agriculture in times when ensuring high-yield productions with limited resources is essential. Methods: In this study, the potential of brewers' spent grain (BSG), the major by-product of the brewing industry, as organic soil amendment, was investigated. Bioprocessed BSG, obtained by an enzymatic treatment coupled with fermentation, together with native BSG, were used as amendments in a pot-trial. An integrated analytical approach aimed at assessing the modification of the physicochemical properties of a typical Mediterranean alkaline agricultural soil, and the plant growth-promoting effect on escarole (Cichorium endivia var. Cuartana), was carried out. Results: The use of biomasses led to soil organic content and total nitrogen content up to 72 and 42% higher, compared to the unamended soils. Moreover, the lower pH and the higher organic acids content doubled phosphorus availability. Although the number of leaves per plant in escaroles from pots amended with native and bioprocessed BSG did not show any difference compared to plants cultivated on unamended pots, the average fresh weight per escarole head, was higher in pots amended with bioprocessed BSG. Discussion: Hence, the results collected so far encourage BSG application for agricultural purpose, while solving the problem of disposing of such abundant side stream

Asymmetric Synthesis and Biological Screening of Quinoxaline-Containing Synthetic Lipoxin A₄ Mimetics (QNX-sLXms)

Failure to resolve inflammation underlies many prevalent pathologies. Recent insights have identified lipid mediators, typified by lipoxins (LXs), as drivers of inflammation resolution, suggesting potential therapeutic benefit. We report the asymmetric preparation of novel quinoxaline-containing synthetic-LXA4-mimetics (QNX-sLXms). Eight novel compounds were screened for their impact on inflammatory responses. Structure–activity relationship (SAR) studies showed that (R)-6 (also referred to as AT-02-CT) was the most efficacious and potent anti-inflammatory compound of those tested. (R)-6 significantly attenuated lipopolysaccharide (LPS)- and tumor-necrosis-factor-α (TNF-α)-induced NF-κB activity in monocytes and vascular smooth muscle cells. The molecular target of (R)-6 was investigated. (R)-6 activated the endogenous LX receptor formyl peptide receptor 2 (ALX/FPR2). The anti-inflammatory properties of (R)-6 were further investigated in vivo in murine models of acute inflammation. Consistent with in vitro observations, (R)-6 attenuated inflammatory responses. These results support the therapeutic potential of the lead QNX-sLXm (R)-6 in the context of novel inflammatory regulators

A Semi-Lagrangian scheme for a modified version of the Hughes model for pedestrian flow

In this paper we present a Semi-Lagrangian scheme for a regularized version of the Hughes model for pedestrian flow. Hughes originally proposed a coupled nonlinear PDE system describing the evolution of a large pedestrian group trying to exit a domain as fast as possible. The original model corresponds to a system of a conservation law for the pedestrian density and an Eikonal equation to determine the weighted distance to the exit. We consider this model in presence of small diffusion and discuss the numerical analysis of the proposed Semi-Lagrangian scheme. Furthermore we illustrate the effect of small diffusion on the exit time with various numerical experiments