Good Estimates Research Articles

Prototype-scale laboratory observations of wave force reduction by an idealized mangrove forest of moderate cross-shore width

A prototype-scale physical model was used to study wave height attenuation through an idealized mangrove forest and the resulting reduction of wave forces and pressures on a vertical wall. An 18 m transect of a Rhizophora forest was constructed using artificial trees, considering a baseline and two mangrove stem density configurations. Wave heights seaward, throughout, and shoreward of the forest and pressures on a vertical wall landward of the forest were measured. Mangroves reduced wave-induced forces by 4%–43% for random waves and 2%–38% for regular waves. For nonbreaking wave cases, the shape of the pressure distribution was consistent, implying that the presence of the forest did not change wave-structure interaction processes. Analytical methods for determining nonbreaking wave-induced loads provided good estimations of measured values when attenuated wave heights were used in equations. The ratio of negative to positive force ranged between 0.14 and 1.04 for regular waves and 0.31 to 1.19 for random waves, indicating that seaward forces can be significant and may contribute to destabilization of seawalls during large storms. These results improve the understanding of wave-vegetation-structure interaction and inform future engineering guidelines for calculating expected design load reductions on structures sheltered by emergent vegetation.

A numerical oxidation model for SiC‐coated thermal protection systems in hypersonic applications

AbstractSilicon carbide (SiC) is a widely used component for thermal protection system (TPS) design. This material is often used either as a coating layer to protect beneath carbon‐based material against oxidation or as a ceramic matrix for composite materials used in the hypersonic leading edges. A numerical equilibrium model for SiC‐coated material ablation is developed in this study to compute the material response of coated TPS in hypersonic relevant aerothermal environment. The developed model is based on an equilibrium approach similar to the carbon graphite oxidation framework for ablative charring materials. The equilibrium wall composition is calculated based on the minimization of the Gibbs free energy. The proposed method can capture numerically the transition from passive to active oxidation while maintaining a low computational cost and good numerical stability. Implementation of the model in the Porous Material Analysis Toolbox based on OpenFOAM code permits to compare against previous literature test cases. By comparing the surface temperature obtained from the model with the experimental data, it is observed that the numerical model gives a good estimation providing accurate surface temperature prediction.

Lag order selection for long-run variance estimation in econometrics

. Estimating the long-run variance (LRV) is crucial for several econometric issues. Constructing reliable heteroskedasticity autocorrelation consistent (HAC) variance-covariance matrices and implementing efficient generalized method of moments (GMM) estimation procedures require a consistent LRV estimate. A good VARHAC estimator (HAC matrix with the spectral density at frequency zero constructed using a VAR spectral estimation) requires accurately estimating the sum of autoregressive (AR) coefficients; however, a criterion that minimizes the innovation variance does not necessarily yield the best spectral estimate. This article implements an optimal VARHAC estimator using an alternative information criterion, considering the bias in the sum of the parameters for the AR estimator of the spectral density at frequency zero.

Domain independent heuristics for online stochastic contingent planning

AbstractPartially observable Markov decision processes (POMDP) are a useful model for decision-making under partial observability and stochastic actions. Partially Observable Monte-Carlo Planning (POMCP) is an online algorithm for deciding on the next action to perform, using a Monte-Carlo tree search approach, based on the UCT algorithm for fully observable Markov-decision processes. POMCP develops an action-observation tree, and at the leaves, uses a rollout policy to provide a value estimate for the leaf. As such, POMCP is highly dependent on the rollout policy to compute good estimates, and hence identify good actions. Thus, many practitioners who use POMCP are required to create strong, domain-specific heuristics. In this paper, we model POMDPs as stochastic contingent planning problems. This allows us to leverage domain-independent heuristics that were developed in the planning community. We suggest two heuristics, the first is based on the well-known $$h_{add}$$ h add heuristic from classical planning, and the second is computed in belief space, taking the value of information into account.

Elucidating the Transport of Electrons and Molecules in a Solid Electrolyte Interphase Close to Battery Operation Potentials Using a Four-Electrode-Based Generator-Collector Setup.

In lithium-ion batteries, the solid electrolyte interphase (SEI) passivates the anode against reductive decomposition of the electrolyte but allows for electron transfer reactions between anode and redox shuttle molecules, which are added to the electrolyte as an internal overcharge protection. In order to elucidate the origin of these poorly understood passivation properties of the SEI with regard to different molecules, we used a four-electrode-based generator-collector setup to distinguish between electrolyte reduction current and the redox molecule (ferrocenium ion Fc+) reduction current at an SEI-covered glassy carbon electrode. The experiments were carried out in situ during potentiostatic SEI formation close to battery operation potentials. The measured generator and collector currents were used to calculate passivation factors of the SEI with regard to electrolyte reduction and with regard to Fc+ reduction. These passivation factors show huge differences in their absolute values and in their temporal evolution. By making simple assumptions about molecule transport, electron transport, and charge transfer reaction rates in the SEI, distinct passivation mechanisms are identified, strong indication is found for a transition during SEI growth from redox molecule reduction at the electrode | SEI interface to reduction at the SEI | electrolyte interface, and good estimates for the transport coefficients of both electrons and redox molecules are derived. The approach presented here is applicable to any type of electrochemical interphase and should thus also be of interest for interphase characterization in the fields of electrocatalysis and corrosion.

Copy-move forgery detection using Regional Density Center clustering

Copy-move forgery detection is a common image tampering detection technology. In this paper, a novel copy-move forgery detection scheme is proposed. The proposed scheme is based on Regional Density Center (RDC) clustering and Refined Length Homogeneity Filtering (RLHF) policy. First, to obtain an adequate number of keypoints in smooth or small areas of the image, the proposed scheme employs scale normalization and adjustment of the contrast threshold of the input image. Subsequently, to speed up the feature matching process, a matching algorithm based on gray value grouping is used to match the keypoints. RLHF policy is applied to filter the mismatched pairs. To guarantee a good estimation of the affine transformation, the RDC clustering algorithm is proposed to group the matched pairs. Finally, the correlation coefficients are computed to precisely locate the tampered regions. The proposed copy-move forgery detection scheme based on RDC and RLHF can effectively identify duplicated regions of digital images. It demonstrates the effectiveness and robustness of the proposed scheme over many state-of-the-art schemes on public datasets.

Lithium Battery SoC Estimation Based on Improved Iterated Extended Kalman Filter

With the application of lithium batteries more and more widely, in order to accurately estimate the state of charge (SoC) of the battery, this paper uses the iterated extended Kalman filter (IEKF) algorithm to estimate the SoC. The Levenberg–Marquardt (LM) method is used to optimize the error covariance matrix of IKEF. Based on the hybrid pulse power characteristics experiment, a second-order Thevenin model with variable parameters is established on the MATLAB platform. The experimental results show that the proposed model is effective under the constant current discharge condition, the Federal Urban Driving Schedule (FUDS) condition, and the Beijing dynamic stress test (BJDST) condition. The results show that the simulation error of the improved LM-IEKF algorithm is less than 2% under different working conditions, which is lower than that of the IKEF algorithm. The improved algorithm has a fast convergence speed to the true value, and it has a good estimation accuracy in the case of large changes in external input current. Additionally, the fluctuation of error is relatively stable, which proves the reliability of the algorithm.

Spatially and temporally differentiated characterization factors for supply risk of abiotic resources in life cycle assessment

Life cycle assessment, a comprehensive tool to evaluate environmental impacts across a product's life cycle, traditionally focuses on "inside-out" impacts caused by the product on the environment, emphasizing resource use, global warming, and other environmental impacts. In contrast, the "outside-in" perspective considers resource availability and accessibility to industry. This second perspective was developed as a way to integrate raw material criticality assessment into LCA. The GeoPolRisk method assesses the supply risk based on global production concentration, import shares, political stability scores, and the average price of the commodity. This article introduces a characterization model for the GeoPolRisk method and calculates the Geopolitical Supply Risk Potential of using 46 raw materials across different countries in multiple years. The characterization factors show the highest values for precious metals, like platinum group metals (PGMs), reflecting their high market prices and concentrated production in geopolitically unstable regions. The results emphasize the significance of spatial and temporal variations in characterization factors, providing a nuanced assessment of supply risk of raw materials associated with the product system. Despite data limitations, the characterization factors offer a good estimate of the supply risk of raw materials available for use in product systems. A case study on photovoltaic laminate production highlights gallium, copper, and tin as significant contributors to supply risk. From an "outside-in" perspective, the case study demonstrates how the GeoPolRisk method complements traditional environmental indicators such as global warming, making it a valuable tool for assessing mineral resource supply risk in Life Cycle Assessment.

WELL-TO-WELL (W2W) ELECTROMAGNETIC TOMOGRAPHY MODELING ADVANCEMENT: IMPROVING PRECISION AND EFFECTIVENESS WITH REGULARIZATION

This research describes the direct and inverse problems of cross-well electromagnetic tomography. The model geometry has azimuthal symmetry, which simplifies the forward modeling and the inversion procedure. In the direct problem, the finite element method is used in the numerical solution of the Helmholtz equation. In the inverse problem, the study discusses the use of three stabilizer functionals: Global Smoothness (GS), Total Variation (TV), and Absolute Equality (AE). The first uses a smoothing function in the L2 norm, while the latter uses smoothing in the L1 norm, for it accepts abrupt changes between adjacent parameters. The results show that the TV method generated good estimates of both geometry and conductivity of the bodies, both for small and large conductivity contrast between the targets and the surrounding environment. Through the results, one can also observe that the regularization of the Total Variation presented a better estimate of the parameters than the Global Smoothness. In most of the synthetic models used in this work, the best estimates of the proposed model occurred when Absolute Equality constraints were used on the cells at the edges of the inversion grid, in addition to the stabilizer functional.

Design and Implementation of a Microstrip Six-Port Reflectometer (SPR) with Enhanced Bandwidth

A compact microstrip six-port reflectometer (SPR) with extended bandwidth is proposed in this paper. The design is based on using 16-dB multi-section coupled line directional couplers and a multi-section 3-dB Wilkinson power divider operating from 1 to 6 GHz. The proposed SPR employs only two calibration standards: a matched load and an open load. As compared to other dielectric substrates, fabricating the proposed SPR involves using a low-cost (FR4) substrate. A novel algorithm is also proposed to estimate the complex reflection coefficient over the frequency ranges at which the standard performance of the circuit components is not fully satisfied. The new algorithm is based on the circles’ intersection points, which have been derived from basic SPR equations, to estimate the complex reflection coefficient. To validate the SPR performance, a multiband microstrip patch antenna has been measured and the resulted reflection coefficient is compared with those obtained using a vector network analyzer (VNA). Results show that the proposed SPR provides a good estimation of the complex reflection coefficient within the frequency range of 1 GHz to 8 GHz. Owing to its compact size and ease of fabrication, the proposed reflectometer is suitable for various microwave broadband applications.

Elastodynamic shape derivative: focus on the sampling of a circular distribution

The detection and quantification of defects plays a crucial role in several industries. Assessing the severity enables to schedule maintenance appropriately, optimizing costs and reducing risks. Guided elastic waves are particularly suitable for Structural Health Monitoring applications on thin structures thanks to their long range and high sensitivity. Guided wave tomography, based on an acoustic propagation hypothesis, has been studied over the last decade to quantitatively image defects in waveguides. The acoustic approximation of this family of methods allows fast computation and good estimation of defects for simple geometries such as plates or pipes. However, this hypothesis induces that a single guided mode is considered, without mode conversion, which limits its use to defects larger than two wavelengths in structures close to ideal waveguides. Hence the need of new imaging algorithms for smaller defects in less ideal structures such as pipes with welded supports. We present here an adaptation of the shape derivative method to ultrasounds in order to reconstruct surface defect on structures with complex geometries. The physical model used is the full elastodynamic problem. It allows taking into account all physical phenomena occuring during wave propagation. Iterative methods such as shape derivative are well known to give precise results but at a high computational cost as the method needs to solve the full elastodynamic problem at each iteration, and a sensitivity to local minima, which may prevent convergence toward the true defect. To suppress these two drawbacks, a spectral finite element method is used to reduce the computation and memory costs. The result of acoustic guided wave tomography is also used as a first guess to reduce the number of iterations and the sensitivity to local minima. After explaining the principle of the shape derivative, validations on simulated and experimental data will be presented in this talk.

Printing path-dependent two-scale models for 3D printed planar auxetics by material extrusion

One particularly interesting class of mechanical metamaterials are those having a negative Poisson’s ratio, which are referred to as ‘auxetics’. Because of their geometrical complexity, auxetic designs cannot always be easily created. However, Additive Manufacturing (AM) methods like material extrusion in 3D printing present the opportunity to construct auxetic structures. Nevertheless, extruded 3D printed material can be highly anisotropic. Before 3D printed auxetics manufactured through material extrusion can be used in engineering applications, it is important to generate powerful simulation tools that can reliably reproduce and foretell their mechanical characteristics irrespective of their form and intricacy. In view of this, the current work proposes printing path-dependent models based on an experimentally validated multi-scale modelling scheme using the Lattice Beam Model (LBM). This is done by first representing idealized microstructures of extruded 3D printed polymers through geometric models and simulating these on the material scale. The aim is to explicitly model the inter-layer and intra-layer bonds that exist in material extruded 3D printed parts by assigning experimentally obtained interface properties that significantly differ from the bulk material. On the auxetic structure scale, two planar auxetic designs are modelled using the determined material scale relationships as input: Re-Entrant (RE) and Rotating Square (RS). In terms of mechanical response, the experimentally and numerically obtained force displacement curves agree reasonably well: the stiffness of the modelled auxetic designs fit well with the experimentally measured ones while the LBM simulations generally provide a good estimation in strength. Finally, it has been shown on both the material and auxetic structure scales that incorporation of the interfacial bond strengths in simulations of extruded 3D printed polymers is important, because neglecting these results in significant overestimation of the strength.

Stability of estimation item parameter in IRT dichotomy considering the number of participants

This research is related to item response theory (IRT) which is needed to measure the goodness of a test set, while item parameter estimation is needed to determine the technical properties of a test item. Stability of item parameter estimation is conducted to determine the minimum sample that can be used to obtain good item parameter estimation results. The purpose of this study is to describe the effect of the number of test takers on the stability of item parameter estimation with the Bayes method (expected a posteriori, EAP) on dichotomous data. This research is an exploratory descriptive research with a bootstrap approach using the EAP method. The EAP method is performed by modifying the likelihood and function to include prior information about the participant's 9 score. Bootstrapping on the original data is done to take bootstrap samples. with ten different sample sizes of 100, 150, 250, 300, 500, 700, 1,000, 1,500, 2,000, 2,500 were then replicated ten times and grain parameter estimation was performed. Each sample data with ten replications was calculated Root Mean Squared Difference (RMSD) value. The results showed that the 2PL model was chosen as the best model. The RMSD value obtained proves that many test participants affect the stability of item parameter estimation on dichotomous data with the 2PL model. The minimum sample to ensure the stability of item parameter estimates with the 2PL model is 1,000 test participants.

Reliability estimation of a multicomponent stress-strength model based on copula function under progressive first failure censoring

In reliability analysis of a multicomponent stress-strength model, most studies assumed independence between stress and strength variable. However, this assumption may not be realistic. To account for dependency, copula approach can be used. Although it is important, only few studies considered this case and usually under complete study. Observing the failures for all units may be difficult due to cost and time limitation. Recently, progressive first failure censoring scheme has attracted attention in the literature due to its ability to save time and money. To the best of our knowledge, dependent multicomponent stress-strength model under progressive first failure censoring was not considered yet. In this article, we derived the likelihood function for progressive first failure censored sample under copula and multicomponent stress strength model. A simulation study is performed and a real dataset is analyzed to test the applicability of the model. Maximum likelihood estimates, asymptotic confidence interval and bootstrap confidence intervals are obtained. The results illustrated that the proposed censoring scheme under copula provides a good estimate for the reliability.

Nondifferentiable activity in the brain.

Spike raster plots of numerous neurons show vertical stripes, indicating that neurons exhibit synchronous activity in the brain. We seek to determine whether these coherent dynamics are caused by smooth brainwave activity or by something else. By analyzing biological data, we find that their cross-correlograms exhibit not only slow undulation but also a cusp at the origin, in addition to possible signs of monosynaptic connectivity. Here we show that undulation emerges if neurons are subject to smooth brainwave oscillations while a cusp results from nondifferentiable fluctuations. While modern analysis methods have achieved good connectivity estimation by adapting the models to slow undulation, they still make false inferences due to the cusp. We devise a new analysis method that may solve both problems. We also demonstrate that oscillations and nondifferentiable fluctuations may emerge in simulations of large-scale neural networks.

Object pose estimation by iterative contacts with soft tactile sensor

In order for a robot to manipulate an object, it is required to estimate the object's pose. The Manifold Particle Filter, an extension of the widely used Particle Filter as a state estimation method, was proposed for the object pose estimation. The Manifold Particle Filter can utilize tactile information, but it has only been applied to binary observations. In this paper, Continuous-MPF, which can use multidimensional and continuous observation information, is proposed. Additionally, we propose an extension of Continuous-MPF, which can store and utilize non-contact information in order to improve the efficiency of estimation. The proposed method was implemented in a robot system and experimentally validated. Good estimation results were obtained for most of the given conditions.

A novel multi-objective optimization strategy based on vibrating particle system algorithm applied to chemical process design

Chemical process design is a highly interesting field within the chemical engineering community due to the numerous potential applications it offers. Traditionally, this problem involves multiple objectives and constraints related to mass, energy, and momentum balances, as well as limitations based on environmental, physical, and operating conditions. Over the past few decades, various multi-objective optimization strategies incorporating evolutionary algorithms have been proposed and tested using test cases of varying complexity. In this study, we propose a new Multi-objective Optimization Vibrating Particle System (MOVPS) algorithm. This numerical strategy extends the Vibrating Particle System Algorithm to a multi-objective context by incorporating three operators into the original algorithm: Pareto dominance, crowding distance, and a mutation strategy. To expedite the convergence process and avoid local optima, an external repository is considered. We evaluate the performance of the proposed methodology by applying it to mathematical functions (ZDT functions) and chemical process design problems. Regarding the ZDT functions, the computational cost (number of objective function evaluations and the processing time) was not increased considering the proposed methodology, as well as the values of convergence and diversity metrics are in agreement with those calculated considering other multi-objective optimization strategies. For most engineering case studies, it was possible to verify that the proposed methodology was able to obtain good estimates for the Pareto curve without increasing the computational cost. However, for the industrial styrene reactor problem it was possible to improve the Pareto curve and reduce the computational cost in relation to other multi-objective optimization algorithms.

Full year performance analysis and steady state operation model for a stationary Shadeless solar thermal collector with a horizontal aperture for steam generation

This work documents a full-year performance of a new design of a non-tracking zero-latitude-tilt external compound parabolic concentrator (XCPC) solar thermal system called Non-tracking Asymmetric Shadeless (NASH) concentrator. The system has a horizontal-aperture design that offers several advantages in terms of land use efficiency because of zero row-to-row spacing, reduced capital costs, and improved heat management. The horizontal aperture (no tilt) design enables it to be scaled to a large area easily without lost area from row-to-row shading as experienced by a tilted design. The system was tested at the University of California Merced, Castle test facility for a full year. The data are analyzed to investigate the system efficiency and thermal energy generated during the year. The system generated 766 kWh/m2 during 2022 with annual efficiency of 41 %. A steady-state model is developed to predict the system performance based on the direct- and diffuse-light optical efficiencies, radiative and manifold heat losses, and observed soiling rate. The system efficiency decreased by up to 14 % over a month due to soiling in this test location. The model gives a good estimation of the steady-state operation during July and predicts the general annual trend of the generated thermal energy.

Validation of EUHFORIA cone and spheromak coronal mass ejection models

We present validation results for calculations of arrival times and geomagnetic impact of coronal mass ejections (CMEs) using the cone and spheromak CME models implemented in EUropean Heliospheric FORecasting Information Asset (EUHFORIA). Validating numerical models is crucial for ensuring their accuracy and performance with respect to real data. We compared CME plasma and magnetic field signatures measured in situ by satellites at the L1 point with the simulation output of EUHFORIA. The validation of this model was carried out using two datasets in order to ensure a comprehensive evaluation. The first dataset focuses on 16 CMEs that arrived at Earth, offering specific insights into the model's accuracy in predicting arrival time and geomagnetic impact. Meanwhile, the second dataset encompasses all CMEs observed over eight months within Solar Cycle 24, regardless of whether or not they arrived at Earth, covering periods of both solar minimum and maximum activity. This second dataset enables a more comprehensive evaluation of the model's predictive precision in term of CME arrivals and misses. Our results show that EUHFORIA provides good estimates in terms of arrival times, with root mean square error (RMSE) values of 9 hours. Regarding the number of correctly predicted ICME arrivals and misses, we find a 75<!PCT!> probability of detection in a 12 hour time window and 100<!PCT!> probability of detection in a 24 hour time window. The geomagnetic impact forecasts measured by the $K_p$ index provide different degrees of accuracy ranging from 31<!PCT!> to 69<!PCT!>. These results validate the use of cone and spheromak CMEs for real-time space weather forecasting.

Development of a universal atomistic cement model incorporating nanomaterials: From laboratory investigation to molecular simulation

Hydrated cement is considered one of the most complex binder systems. The development of models that suitably represent hydrated cement is still far from established due to the complexity of the hydration process, as well as the multiscale phase and different morphological properties. Therefore, this study attempts to develop a hydrated cement model using molecular-level simulation and laboratory testing. This model aimed to predict the mechanical properties of cement paste between 0.25 and 0.65 w/c ratios. In this regard, five cement paste mixtures with various w/c ratios were prepared and tested to evaluate their mechanical properties and micro-structures. Then, a novel modeling methodology using molecular dynamics (MD) simulation was carried out to develop an ingredient-based atomistic cement model. In this regard, the Dreiding force field (DFF) was used in all the simulation processes, starting from the cement clinker phases to the hydrated cement. The experimental results of cement paste mixtures revealed some useful data that was supportive of the simulations. Radial distribution function (RDF) and fractional free volume (FFV) were utilized to investigate the local atomic structure of the cement paste models. The calcium-silicate-hydrated (C–S–H) of the developed model was characterized through RDF and benchmarked to a well-known mineral analog, namely tobermorite. The developed model was computationally tested under different w/c ratios, and reliable results in terms of micro-structural matrix as well as mechanical properties were obtained. Then, the cement models incorporating different ratios of nano-silica were developed, and a good estimation of the mechanical properties was obtained. Because of the universal nature of the reported model in this research, it could be utilized to further predict the mechanical behavior and durability performance of the cement paste.