Local Response Function Research Articles

Estimating bridge stress histories at remote locations from vibration sparse monitoring

Structural health monitoring with accelerometers provides notable benefits over strain gauges, particularly in installation time and cost efficiency. However, effective local damage assessment necessitates access to local stress histories. This paper proposes a methodology that integrates two distinct approaches to identify and predict stress and strain across various bridge locations from sparse monitoring via acceleration data. The proposed model is validated using strain histories and accelerations collected from the composite railway Bryngeån Bridge in Sweden during its in-service conditions. Initially, a deep learning algorithm for sequence data is employed to forecast strain histories from acceleration data gathered across various bridge locations. Subsequently, the local response function method is implemented, utilizing experimental data collected from the bridge and employing localized models of its substructures, allowing predictions of the bridge’s local strain. By integrating these methods, the approach enables accurate prediction of stress ranges and cycles for critical non-instrumented parts, minimizing the need for extensive direct instrumentation and providing a cost-effective, efficient solution for operational structural health monitoring.

P38 Experimental evidence of ecto-5′-nucleotidase (CD73) modulation in psoriasis-like inflammation

Abstract Introduction and aims Adenosine is an endogenous purine nucleoside that, by binding to adenosine receptors, modulates inflammation and immune responses. Psoriasis is a chronic immune-mediated inflammatory skin disease characterized by keratinocyte hyperproliferation and abnormal differentiation. A2A and A2B adenosine receptors modulate keratinocyte proliferation and their expression was found to be altered in psoriatic epidermis. Ecto-5′-nucleotidase (CD73) is an enzyme that hydrolyses extracellular adenosine monophosphate and represents a key control point for extracellular adenosine accumulation. CD73 is involved in the regulation of local immune response and tissue barrier function. As changes in CD73 expression and activity have been associated with other autoimmune diseases, the aim of this study was to investigate CD73 involvement in skin inflammation using in vitro and in vivo approaches. Methods In vitro experiments were performed on human keratinocyte (HaCaT) cell lines stimulated with tumour necrosis factor-α, interleukin (IL)-17A, IL-6 and IL-1α (10 ng mL−1 each), and in vivo, on the mouse model of imiquimod-induced psoriasis-like inflammation on the right ear, which was also performed on CD73−/− mice and their wildtype counterpart. CD73 expression in cell lysates and ear homogenates were evaluated using Western blot analysis. Results We found that CD73 expression was significantly increased (N = 3 wells, P < 0.05) in cytokine-treated HaCaTs compared with unstimulated cells. In vivo experiments showed increased CD73 expression on psoriatic lesions (P < 0.001, N = 3). In CD73−/− mice, imiquimod-induced lesions were exacerbated compared with the development of lesions in wildtype mice as shown by ear thickness (0.190 ± 0.02 mm, knockout mice vs. 0.138 ± 0.02 mm, wildtype mice; P < 0.05, N = 5), erythema and scaling. Conclusions Our preliminary Results show involvement of CD73 in the development of psoriasis-like inflammation, suggesting that CD73 may represent a new therapeutic target in the treatment of skin diseases. Further investigations are needed to provide an in-depth study of CD73 localization in inflamed skin.

Virtual Sensing in Steel Bridges: Time Series Deep Learning for Stress Prediction

This study introduces an innovative approach for predicting stress responses in steel bridges, specifically focusing on a railway bridge in Vänersborg, Sweden. Four deep learning models have been evaluated: Multilayer Perceptron (MLP), Long Short-Term Memory (LSTM), Temporal Convolutional Network (TCN), and a hybrid LSTM-TCN. Training on stress history data from a multiscale Finite Element (FE) model and a validation with real-world data from a bridge monitoring system revealed high prediction accuracy near sensor locations, surpassing an R-squared score of 0.9, comparable to the polynomial local response function method.The comparative analysis provides critical insights into the great potential of deep learning-based sequence models for identifying intricate, temporally dependent stress patterns across the bridge, including predictions at points distant from direct sensor measurements. These models demonstrate a notable capability for capturing highly non-linear relationships between stress histories. While sequence models (LSTM, TCN, and hybrid LSTM-TCN) tended to provide conservative estimates impacting fatigue life predictions, the MLP model occasionally underestimated critical stress cycles.This research emphasizes the potential of deep learning techniques for time series to enhance bridge monitoring systems, improve virtual sensing, and enable real-time monitoring capabilities. Our proposed methodology provides a comprehensive understanding of stress data in steel bridges, which is crucial for ensuring their maintenance and safety.

An adaptive fringe projection method for 3D measurement with high-reflective surfaces

Fringe projection profilometry (FPP) has the advantages of non-contact, quick and high accuracy, which is popular in the fields of industrial inspection and measurement. However, the coded fringe patterns may be failure suffered from the high reflectivity of the measured surfaces. Aiming at this problem, an adaptive fringe projection method is proposed in this paper by the best projection intensity strategy and the coordinate mapping establishment between camera and projection regions. Combining the local camera response function, the dichotomizing search is used to confirm the best projection intensity of overexposed regions by pixel-wise. The unwrapping phase map of background is performed to establish the coordinate mapping relationship of measured overexposed regions between the camera and projection images, which is robust and convenient. The mapping errors caused by inaccurate phase information in the overexposed regions are effectively avoided, and the fringe projection patterns are adjusted adaptively, without additional equipment and low-expose patterns. Both theory and experiments have verified the feasibility and superiority of the proposed method.

A flexible gyro-fluid system of equations

Gyro-fluid equations are velocity space moments of the gyrokinetic equations. Special gyro-Landau-fluid closures have been developed that include the damping due to kinetic resonances by fitting to the collisionless local plasma response functions. This damping allows for accurate linear eigenmodes to be computed with a relatively low number of velocity space moments compared to the number of velocity quadrature points in gyrokinetic codes. However, none of the published gyro-Landau-fluid closure schemes considers the Onsager symmetries of the resulting quasi-linear fluxes as a constraint. Onsager symmetry guarantees that the matrix of diffusivities is positive definite, an important property for the numerical stability of a transport solver. A two parameter real closure for improving the accuracy of low resolution gyro-fluid equations, which preserves the Onsager symmetry and allows higher velocity space moments, is presented in this paper. The new linear gyro-fluid system (GFS) is used to extend the TGLF quasi-linear transport model so that it can compute the energy and momentum fluxes due to parallel magnetic fluctuations, completing the transport matrix. The GFS equations do not use a bounce average approximation. The GFS equations are fully electromagnetic with general flux surface magnetic geometry, pitch angle scattering for electron collisions, and subsonic equilibrium toroidal rotation. Using GFS eigenmodes in the quasi-linear TGLF model will be shown to yield a more accurate match to fluxes computed by CGYRO turbulence simulations. Prospects for future applications of a quasi-linear theory to new plasma transport regimes and magnetic confinement devices in addition to tokamaks are opened by the flexibility of the GFS eigensolver.

A local response function approach for the stress investigation of a centenarian steel railway bridge

Local stress concentrations in some specific geometric details often play an essential role in time-dependent damage propagation. However, measured strain or stress data are generally available in locations that are not the most critical ones. Proper numerical models are thus required to aid the damage severity assessment. In this paper, a surrogate model procedure based on the local response function method is proposed to accurately predict stress time histories in particular regions of bridges through a multiscale numerical analysis. The methodology is calibrated on the basis of direct strain measurements on a railway bridge in Vänersborg, Sweden. The bridge is currently monitored with a set of strain gauges, accelerometers, and an inclinometer allowing the investigation of its in-service conditions during the train passages and the lifting of the bascule truss. The results show the reliability of the method for stress prediction in specific regions of the bridge without the availability of directly measured data together with more detailed knowledge about the stress histories that could lead to fatigue or corrosion damage.

Surface Resistance and Amplitude Mode under Uniform and Static External Field in Conventional Superconductors

We calculate the surface resistance of s-wave superconductors under a static external field on the basis of the quasiclassical approximation. The numerical calculations are performed both for the dirty and relatively clean cases, and the difference in the absorption spectrum between them is investigated. The amplitude mode in the dirty case, which has been previously studied in the local response function, appears also in the nonlocal response. In the clean case, there is a large discrepancy between the excitation energy of the amplitude mode and the energy of the gap edge where the coupling between the electrons and the external field is effective. Therefore, the amplitude mode exists even when the superconductor is relatively clean, but its contribution to the response function is small. These behaviors, which are qualitatively consistent with the experimental results, are obtained by taking into account the static field nonperturbatively.

Fulfillment of sum rules and Ward identities in the multiloop functional renormalization group solution of the Anderson impurity model

We investigate several fundamental characteristics of the multiloop functional renormalization group (mfRG) flow by hands of its application to a prototypical many-electron system: the Anderson impurity model (AIM). We first analyze the convergence of the algorithm in the different parameter regions of the AIM. As no additional approximation is made, the multiloop series for the local self-energy and response functions converge perfectly to the corresponding results of the parquet approximation (PA) in the weak- to intermediate-coupling regime. Small oscillations of the mfRG solution as a function of the loop order gradually increase with the interaction, hindering a full convergence to the PA in the strong-coupling regime, where perturbative resummation schemes are no longer reliable. By exploiting the converged results, we inspect the fulfillment of (i) sum rules associated to the Pauli principle and (ii) Ward identities related to conservation laws. For the Pauli principle, we observe a systematic improvement by increasing the loop order and including the multiloop corrections to the self-energy. This is consistent with the preservation of crossing symmetries and two-particle self-consistency in the PA. For the Ward identities, we numerically confirm a visible improvement by means of the Katanin substitution. At weak coupling, violations of the Ward identity are further reduced by increasing the loop order in mfRG. In this regime, we also determine the precise scaling of the deviations of the Ward identity as a function of the electronic interaction. For larger interaction values, the overall behavior becomes more complex, and the benefits of the higher-loop terms are mostly present in the contributions at large frequencies.

Casimir effect for magnetic media: Spatially nonlocal response to the off-shell quantum fluctuations

We extend the Lifshitz theory of the Casimir force to the case of two parallel magnetic metal plates possessing a spatially nonlocal dielectric response. By solving Maxwell equations in the configuration of an electromagnetic wave incident on the boundary plane of a magnetic metal semispace, the exact surface impedances are expressed in terms of its magnetic permeability and longitudinal and transverse dielectric functions. This allows application of the Lifshitz theory with reflection coefficients written via the surface impedances for calculation of the Casimir pressure between magnetic metal (Ni) plates whose dielectric responses are described by the alternative nonlocal response functions introduced for the case of nonmagnetic media. It is shown that at separations from 100 to 800~nm the Casimir pressures computed using the alternative nonlocal and local plasma response functions differ by less than 1\%. At separations of a few micrometers, the predictions of these two approaches differ between themselves and between that one obtained using the Drude function by several tens of percent. We also compute the gradient of the Casimir force between Ni-coated surfaces of a sphere and a plate using the alternative nonlocal response functions and find a very good agreement with the measurement data. Implications of the obtained results determined by the off-shell quantum fluctuations to a resolution of long-standing problems in the Casimir physics are discussed.

Beta-1 blocker reduces inflammation and preserves intestinal barrier function after open abdominal surgery

Rationale: Open abdominal surgery is frequently associated with excessive inflammatory response and intestinal barrier compromise, leading to the poor clinical outcome. Previously, administration of beta-1 blocker has been shown to effectively reduce inflammation and preserve intestinal barrier function, and the underlying mechanism may be associated with the activation of the autonomic nervous system via cholecystokinin-receptors.This study investigates the effect of beta-1 blocker on the systemic and local inflammatory response and intestinal barrier function in a setting of open abdominal surgery.

Spatial variability of crop responses to agronomic inputs in on-farm precision experimentation

Within-field variability of crop yield levels has been extensively investigated, but the spatial variability of crop yield responses to agronomic treatments is less understood. On-farm precision experimentation (OFPE) can be a valuable tool for the estimation of in-field variation of optimal input rates and thus improve agronomic decisions. Therefore, the objectives of this study were to investigate the spatial variability of optimal input rates in OFPE and the potential economic benefit of site-specific input management. Mixed geographically weighted regression (GWR) models were used to estimate local yield response functions. The methodology was applied to investigate the spatial variability in corn response to nitrogen and seed rates in four cornfields in Illinois, USA. The results showed that spatial heterogeneity of model parameters was significant in all four fields evaluated. On average, the RMSE of the fitted yield decreased from 1.2 Mg ha−1 in the non-spatial global model to 0.7 Mg ha−1 in the GWR model, and the r-squared increased from 10 to 68%. The average potential gain of using optimized uniform rates of seed and nitrogen was US$ 65.00 ha−1, while the added potential gain of the site-specific application was US$ 58.00 ha−1. The combination of OFPE and GWR proved to be an effective tool for testing precision agriculture’s central hypothesis of whether optimal input application rates display adequate spatial variability to justify the costs of the variable rate technology itself. The reported results encourage more research on response-based input management recommendations instead of the still widespread focus on yield-based algorithms.

Study of organic reactions using chemical reactivity descriptors derived through a temperature-dependent approach

Using the ratio of two fluctuations in the temperature-dependent density functional theory, the local counterpart of a global response function and the linear (non-local) counterpart of a local response function can be constructed. Here, we analyze the local chemical potential, local hardness, Fukui kernel and dual descriptor kernel and test their performance for describing and interpreting reactivity features for a diverse set of organic chemical reactions, including acid–base reactions, aliphatic nucleophilic substitutions, aromatic electrophilic substitutions and Markovnikov additions. Despite important differences in size and functionalization between some substrates belonging to a given chemical reaction type, temperature-dependent chemical reactivity descriptors were able to reproduce experimental or computational trends in all cases. We identify relevant chemical interactions belonging to a particular family of reactions and the molecular moieties responsible for such interactions. In general, our results are consistent with traditional chemical interpretations. However, in some cases the information contained in the temperature-dependent chemical reactivity descriptors allows one to gain new insights about the organic chemistry reactions considered here.

On the Diversity of Long-Term Temperature Responses to Varying Levels of Solar Activity at Ten European Observatories

We analyze ten of the longest (127 to 230 year-long) time series of European daily temperatures available from five different Koppen-Geiger climate classes. We split these according to the level of solar cycle activity (H for “higher than median” and L for “lower than median”). This reveals coherent patterns in the temperature differences: when TH-TL are stacked according to their calendar date, the daily averages from January 1 to December 31st disclose characteristic features in addition to the dominant annual seasonal wave, namely variations up to 2°C lasting for about 1.5 to 3 months. The five observatories at intermediate latitudes in a band from Oxford in the West to Prague in the East (same climate class) have very similar signatures. These similarities are most unlikely to be due to pure chance (confirmed by confidence levels in excess of 99% with the Kolmogorov-Smirnov and Kuiper nonparametric tests). The TH-TL patterns carry a regional signature, modulated by a more local response function. On the other hand, northern European observatories (St Petersburg and Arkhangelsk), those south of the Alps (Milan and Bologna), and the easternmost one in Astrakhan, corresponding to different climate classes, have different signatures. Similarly, preliminary study of long air pressure recordings confirms what emerges from the analysis of temperatures. These new observations lead us to conclude that the climate in different regions presents different responses to variations in solar activity. Moreover, the distributions of the lower, middle, and higher quartiles of the temperature and pressure indices in solar cycles with high versus low activity are significantly different, providing further robust statistical confirmation to this conclusion (confidence level higher to much higher than 99% using the Kuiper test).

Stochastic Elasto-Plastic Analysis of Necking Bar with Random Tvergaard Coefficients

This paper reports on the computational modelling of static extension tests of the round steel bar. The main objective was to apply the generalised stochastic perturbation technique implemented as the Stochastic Finite Element Method to carry out the numerical simulation of its elasto-plastic behaviour. This approach was based on: the general order Taylor expansion of all input random variables and the resulting state functions of their average means, as well as on the Least Squares Method employed to determine analytical functions of in-between design parameters and the given structural responses. Tvergaard coefficients were assumed as the uncorrelated Gaussian random variables to check the effect of material porosity uncertainty on the statistical scattering of its deformations and stresses. The computational implementation employed the FEM system ABAQUS and computer algebra system MAPLE, including polynomial and non-polynomial local response functions of the displacements, plastic strains and reduced stresses. Moreover, 4-node axisymmetric, continuum, reduced-integration FEM elements (CAX4R) were used in the conducted analyses. The basic probabilistic characteristics of the structural response (expectations, coefficients of variation, skewness and kurtosis) were determined throughout the entire deformation process as the functions of input uncertainty level. The obtained results were finally contrasted with the classical Monte-Carlo Simulation scheme and the semi-analytical technique for input coefficient of variation of porous plasticity coefficients not larger than 0.20.

The effects of markets, uncertainty and search intensity on bitcoin returns

We review the literature and examine the effects of shocks on bitcoin returns. We assess the effects of factors such as stock market returns, exchange rates, gold and oil returns, FED's and ECB's rates and internet trends on bitcoin returns. Alternative VAR and FAVAR models are employed and generalized as well as local impulse response functions are produced. Our results reveal (i) a significant interaction between bitcoin and traditional stock markets, (ii) a weaker interaction with FX markets and the macroeconomy and (iii) an anemic importance of popularity measures. Lastly, we reveal the increased impact of Asian markets on bitcoin compared to other geographically-defined markets, which however appears to have waned in the last two years after the Chinese regulatory interventions and the sudden contraction of CNY's share in bitcoin trading volume.

Bond-level deformation gradients and energy averaging in peridynamics

Peridynamic models that aim to incorporate a given classical local continuum stress-deformation response function typically start with a nonlocal averaged analog to the deformation gradient as input to the given local stress-deformation response function. This approach has been observed to allow unphysical deformations such as interpenetration and cause loss of linear stability. This paper describes an approach to deal with this shortcoming. The strategy is based on (1) defining a bond-level analog to the deformation gradient tensor – in contrast to the usual vector deformation measure in peridynamics – that captures both the average deformation in the neighborhood of the bond as well as the deviation of the bond stretch from this average deformation, and (2) using this bond-level deformation gradient in the classical local strain energy response to obtain the energy of each bond. Compared to the standard approach that applies the energy to the averaged deformation gradient, this approach instead averages the energy applied to the bond-level deformation gradient.

Revisiting the macroeconomic effects of labor reallocation

We revisit the macroeconomic effects of labor reallocation within the framework of Campbell and Kuttner (1996). We re-estimate their model, update the sample, and employ generalized and local impulse response functions. We confirm that total employment responses to reallocation shocks remain significant.

Stochastic higher order finite element elasto-plastic analysis of the necking phenomenon

The principal goal of this work is to investigate an application of the stochastic perturbation technique of the 10th order in coupled thermo-elasto-plastic analysis of tension of the steel elastic bar exposed to fire with thermally dependent material characteristics. An ambient temperature, calculated from the fire curve after ISO 834-1, equivalent to the fire exposure of the steel structure is treated here as the input Gaussian random variable. It is uniquely defined by the constant mean value at outer surfaces of this element, where material parameters of the steel as Young modulus, yield strength, heat conductivity, capacity and thermal elongation are considered all as highly temperature-dependent. Computational implementation known as the Stochastic Finite Element Method is carried out with the use of the FEM system ABAQUS and computer algebra system MAPLE. It uses both polynomial and non-polynomial local response functions of stresses and displacements. The basic probabilistic characteristics of time-dependent structural response are determined (expectations, coefficients of variation, skewness and kurtosis) and verified with classical Monte-Carlo simulation scheme and semi-analytical technique for input coefficient of variation not larger than 0.20. Finally, probabilistic convergence of all three methods versus increasing input uncertainty level is investigated.

Control of ultrafast plasmon pulses by spatiotemporally phase-shaped laser pulses

We numerically demonstrate that spatially and temporally phase-shaped ultrafast laser pulses can spatiotemporally control ultrafast plasmon pulses generated at metal nanostructures. Excitation laser pulses designed by the superposition of high-order Hermite–Gaussian modes can localize the plasmon excitation at desired areas in nanostructures, and at the same time the temporal plasmon evolution is determined by the excitation pulse shape and the local plasmon response function. We numerically demonstrate this control scheme for local plasmons at the Au nanostructures and a surface plasmon polariton waveguide.

Determination of local optical response functions of nanostructures with increasing complexity by using single and coupled Lorentzian oscillator models

We reconstruct the optical response of nanostructures of increasing complexity by fitting interferometric time-resolved photoemission electron microscopy (PEEM) data from an ultrashort (21 fs) laser excitation source with different harmonic oscillator-based models. Due to its high spatial resolution of ~40 nm, PEEM is a true near-field imaging system and enables in normal incidence mode a mapping of plasmon polaritons and an intuitive interpretation of the plasmonic behaviour. Using an actively stabilized Mach–Zehnder interferometer, we record two-pulse correlation signals with 50 as time resolution that contain information about the temporal plasmon polariton evolution. Spectral amplitude and phase of excited plasmon polaritons are extracted from the recorded phase-resolved interferometric two-pulse correlation traces. We show that the optical response of a plasmon polariton generated at a gold nanoparticle can be reconstructed from the interferometric two-pulse correlation signal using a single harmonic oscillator model. In contrast, for a corrugated silver surface, a system with increased plasmonic complexity, in general an unambiguous reconstruction of the local optical response based on coupled and uncoupled harmonic oscillators, fails. Whereas for certain local responses different models can be discriminated, this is impossible for other positions. Multidimensional spectroscopy offers a possibility to overcome this limitation.