Refinement Approach Research Articles

Accurately Quantifying Stress during Metal Halide Perovskite Thin Film Formation.

The role of strain in metal halide perovskite (MHP) solar cells is still under investigation, showing both beneficial and detrimental effects on the device performance and stability. One crucial component to elucidating the impact of strain in the MHP absorber is a robust method of quantifying the amount of strain in the material. Here, we present a parametric refinement approach based on grazing incidence wide-angle X-ray scattering and demonstrate its use on quantifying strain during thermal annealing and subsequent cooling as a function of substrate and processing route. We use the analysis to reveal the impact of the cubic-to-tetragonal phase transition during cooling on the material's strain and discuss texture formation as a potential strain-relief mechanism. Thereby we present both a robust approach to quantify strain in MHPs and potential mechanisms to control strain in the film, opening the path for further investigations of strain in MHPs.

Smart systems of open science in teachers’ education

The project announced by the authors is focused on the smart systems of open science, the issues of elaboration of methodological, methodic, and organizational support for the use of these emerging ICT in teaching and research, increasing the level of ICT competence of educators, including teachers. Given the significant pedagogical potential and novelty of existing approaches to the use of smart learning systems meaning first of all the cloud-based adaptive open science systems, their design and use in educational institutions, these issues still need theoretical and experimental research, refinement of approaches, models, methods and techniques, possible ways of implementation. In the process of studying leading experience, the following advantages of using the cloud-based services for teachers’ training were identified: resource savings, access mobility, elasticity, and others. The cloud-based methodological system for educational personnel training at different levels was proposed and considered: for the training of students for the Master level for educational sciences; for the in-service teachers’ training. The methods and tools of smart systems design and implementation were considered and evaluated. The recommendations and suggestions for the advisable ways for smart systems of open science introduction into the learning process were provided.

A refinement approach to the multivariable tracking error problem

This article presents a new refinement design routine aimed at solving the robust multivariable tracking error problem with reduced conservatism. The prevailing multivariable quantitative feedback theory (QFT) approach is to implicitly overbound the model-error tracking set frequency response in magnitude using the triangle inequality, with the intention of arriving at a set of univariate design constraints that independently describe the feedback controller solution space. While this method is effective in the low-frequency range (where the loop gain tends to be large), the mid- to high-frequency design regions (where diagonal dominance is not possible in general) suffers from arbitrarily large design conservatism. This inhibits minimum gain-phase solutions and necessitates undesirable over-design in the frequency band that can contribute to large, expensive control action. The proposed method follows a refinement approach that makes use of information from an a priori feedback control design. In this way, the tracking error problem is reposed as a differential design, and gain-phase information from the previous iteration can be captured to reduce the conservatism imposed when applying the triangle inequality. Additionally, a constrained optimization routine is used to select a prototype feedforward filter that can relax the constraint set, thereby increasing the accessible solution space of the diagonal feedback controller. Finally, a nondiagonal, multivariable feedforward filter bound generation routine is defined that relies on existence conditions and is free of induced design conservatism. The viability of this design methodology is demonstrated on two benchmark problems of varying complexity, in order to demonstrate the widespread efficacy.

Biodegradable polyurethane scaffolds in regenerative medicine: Clinical translation review.

Early explorations of tissue engineering and regenerative medicine concepts commonly utilized simple polyesters such as polyglycolide, polylactide, and their copolymers as scaffolds. These biomaterials were deemed clinically acceptable, readily accessible, and provided processability and a generally known biological response. With experience and refinement of approaches, greater control of material properties and integrated bioactivity has received emphasis and a broadened palette of synthetic biomaterials has been employed. Biodegradable polyurethanes (PUs) have emerged as an attractive option for synthetic scaffolds in a variety of tissue applications because of their flexibility in molecular design and ability to fulfill mechanical property objectives, particularly in soft tissue applications. Biodegradable PUs are highly customizable based on their composition and processability to impart tailored mechanical and degradation behavior. Additionally, bioactive agents can be readily incorporated into these scaffolds to drive a desired biological response. Enthusiasm for biodegradable PU scaffolds has soared in recent years, leading to rapid growth in the literature documenting novel PU chemistries, scaffold designs, mechanical properties, and aspects of biocompatibility. Despite the enthusiasm in the field, there are still few examples of biodegradable PU scaffolds that have achieved regulatory approval and routine clinical use. However, there is a growing literature where biodegradable PU scaffolds are being specifically developed for a wide range of pathologies and where relevant pre-clinical models are being employed. The purpose of this review is first to highlight examples of clinically used biodegradable PU scaffolds, and then to summarize the growing body of reports on pre-clinical applications of biodegradable PU scaffolds.

The Refinement of Petri Net with Inhibitor Arcs Based Representation for Embedded Systems

Embedded systems are widely used in various devices. PRES+ (Petri net- based Representation for Embedded Systems) has been used to model and analyze embedded systems. However, it cannot characterize the priority of events, and cannot fully express the complex data flow and control flow. To solve this problem, inhibitor arcs are added to PRES+ and PIRES+ (PRES+ with Inhibitor arcs) is obtained. However, PIRES+’s state space explosion problem is a handicap when modeling, verifying, and controlling complex, large embedded systems. To mitigate the state space explosion problem of PIRES+ and analyze complex embedded systems, we propose the place refinement approach and the place set refinement approach for PIRES+. Under specific conditions, several important properties of PIRES+, such as timing, functionality, reachability, liveness, and boundedness, are preserved by using these refinement approaches. In order to illustrate the effectiveness of these refinement methods, as an example, the modeling and analysis of a network communication system is proposed. The refinement methods proposed have certain feasibility and practicability and provide a more practical theoretical basis for the modeling of some embedded systems.

Towards convergence of turbulent dynamo amplification in cosmological simulations of galaxies

ABSTRACT Our understanding of the process through which magnetic fields reached their observed strengths in present-day galaxies remains incomplete. One of the advocated solutions is a turbulent dynamo mechanism that rapidly amplifies weak magnetic field seeds to the order of ∼$\mu$G. However, simulating the turbulent dynamo is a very challenging computational task due to the demanding span of spatial scales and the complexity of the required numerical methods. In particular, turbulent velocity and magnetic fields are extremely sensitive to the spatial discretization of simulated domains. To explore how refinement schemes affect galactic turbulence and amplification of magnetic fields in cosmological simulations, we compare two refinement strategies. A traditional quasi-Lagrangian adaptive mesh refinement approach focusing spatial resolution on dense regions, and a new refinement method that resolves the entire galaxy with a high resolution quasi-uniform grid. Our new refinement strategy yields much faster magnetic energy amplification than the quasi-Lagrangian method, which is also significantly greater than the adiabatic compressional estimate indicating that the extra amplification is produced through stretching of magnetic field lines. Furthermore, with our new refinement the magnetic energy growth factor scales with resolution following $\propto {\Delta x}_\text{max}^{-1/2}$, in much better agreement with small-scale turbulent box simulations. Finally, we find evidence suggesting most magnetic amplification in our simulated galaxies occurs in the warm phase of their interstellar medium, which has a better developed turbulent field with our new refinement strategy.

Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition

In wearable-based human activity recognition (HAR) research, one of the major challenges is the large intra-class variability problem. The collected activity signal is often, if not always, coupled with noises or bias caused by personal, environmental, or other factors, making it difficult to learn effective features for HAR tasks, especially when with inadequate data. To address this issue, in this work, we proposed a Behaviour Pattern Disentanglement (BPD) framework, which can disentangle the behavior patterns from the irrelevant noises such as personal styles or environmental noises, etc. Based on a disentanglement network, we designed several loss functions and used an adversarial training strategy for optimization, which can disentangle activity signals from the irrelevant noises with the least dependency (between them) in the feature space. Our BPD framework is flexible, and it can be used on top of existing deep learning (DL) approaches for feature refinement. Extensive experiments were conducted on four public HAR datasets, and the promising results of our proposed BPD scheme suggest its flexibility and effectiveness. This is an open-source project, and the code can be found at http://github.com/Jie-su/BPD

Synthesis of strategies for autonomous surveillance on adversarial targets

We study the problem of synthesizing a controller for an agent with imperfect sensing and a quantitative surveillance objective, that is, an agent is required to maintain knowledge of the location of a moving, possibly adversarial target. We formulate the problem as a one-sided partial-information game with a winning condition expressed as a temporal logic specification. The specification encodes the quantitative surveillance requirement as well as any additional tasks. Solving a partial-information game typically involves transforming it into a perfect-information belief game using a belief-set construction. Such a transformation leads to a state-space explosion, rendering the belief game computationally intractable to solve for most realistic settings. We present a belief-set abstraction technique to transform the partial-information game to a provably sound abstract belief game that can be solved efficiently using off-the-shelf reactive synthesis tools. We introduce a counterexample-guided refinement approach to automatically achieve the abstraction precision sufficient to synthesize a strategy that is provably winning on the original partial-information game. We evaluate the proposed method on multiple case-studies, implemented on hardware as well as high-fidelity ROS/Gazebo simulations where the agent must respond in real-time to a human-controlled adversary.

Exploring high-resolution cryo-ET and subtomogram averaging capabilities of contemporary DEDs

The potential of energy filtering and direct electron detection for cryo-electron microscopy (cryo-EM) has been well documented. Here, we assess the performance of recently introduced hardware for cryo-electron tomography (cryo-ET) and subtomogram averaging (STA), an increasingly popular structural determination method for complex 3D specimens. We acquired cryo-ET datasets of EIAV virus-like particles (VLPs) on two contemporary cryo-EM systems equipped with different energy filters and direct electron detectors (DED), specifically a Krios G4, equipped with a cold field emission gun (CFEG), Thermo Fisher Scientific Selectris X energy filter, and a Falcon 4 DED; and a Krios G3i, with a Schottky field emission gun (XFEG), a Gatan Bioquantum energy filter, and a K3 DED. We performed constrained cross-correlation-based STA on equally sized datasets acquired on the respective systems. The resulting EIAV CA hexamer reconstructions show that both systems perform comparably in the 4–6 Å resolution range based on Fourier-Shell correlation (FSC). In addition, by employing a recently introduced multiparticle refinement approach, we obtained a reconstruction of the EIAV CA hexamer at 2.9 Å. Our results demonstrate the potential of the new generation of energy filters and DEDs for STA, and the effects of using different processing pipelines on their STA outcomes.

Capturing the flame structure and the transition process of the fire whirl using two combustion kinetic considerations

PurposeThe purpose of this paper is to investigate the development process of the fire whirl in the fixed-frame facility and focus on the impacts of the fire whirl’s vortex core on the formation and flame structure of the fire whirl.Design/methodology/approachThe complex turbulent reacting flame surface is captured by the large eddy simulation turbulence closure coupled with two sub-grid scale (SGS) kinetic schemes (i.e. the chemistry equilibrium and steady diffusion flamelet). Numerical predictions are validated thoroughly against the measurements by Lei et al. (2015) with excellent agreements. A double maximum tangential velocity refinement approach is proposed to quantify the vortex cores’ instantaneous location and region, addressing the missing definition in other studies.FindingsThe numerical results show that the transition process of the fire whirl is dominated by the vortex core movement, which is related to the centripetal force. The unsteadiness of the fully developed fire whirl was found depending on the instantaneous fluctuation of heat release rate. The steady diffusion flamelet scheme is essential to capture the instantaneous fluctuation. Furthermore, the axial velocity inside the vortex core is the key to determining the state of fire whirl.Practical implicationsDue to intensive interactions between buoyant fires and ambient rotating flow, the on-set and formation of fire whirl still remain largely elusive. This paper focused on the transition process of fire whirl between different development stages. This paper provides insights into the transition process from the inclined flame to the fire whirls based on the centripetal force.Originality/valueThis paper presented and compared two SGS kinetic schemes to resolve the fire whirl development process and the unsteadiness of its vortical structures. The modelling framework addresses the shortcoming of previous numerical studies where RANS turbulence closure and simplified combustion kinetics was adopted. Numerical results also revealed the fire whirl transition process and its relationship to centripetal force.

Adaptive Model Refinement Approach for Bayesian Uncertainty Quantification in Turbulence Model

The Bayesian uncertainty quantification technique has become well-established in turbulence modeling over the past few years. However, it is computationally expensive to construct a globally accurate surrogate model for Bayesian inference in a high-dimensional design space, which limits uncertainty quantification for complex flow configurations. Borrowing ideas from stratified sampling and inherited sampling, an adaptive model refinement approach is proposed in this work, which concentrates on asymptotically improving the local accuracy of the surrogate model in the high-posterior-density region by adaptively appending model evaluation points. To achieve this goal, a modification of inherited Latin hypercube sampling is proposed and then integrated into the Bayesian framework. The effectiveness and efficiency of the proposed approach are demonstrated through a two-dimensional heat source inversion problem and its extension to a high-dimensional design space. Compared with the prior-based method, the adaptive model refinement approach has the ability to obtain more reliable inference results using fewer evaluation points. Finally, the approach is applied to parametric uncertainty quantification of the Menter shear-stress transport turbulence model for an axisymmetric transonic bump flow and provides convincing numerical results.

Trajectory-Based Skill Learning for Overhead Construction Robots Using Generalized Cylinders with Orientation

Overhead work involving the construction and maintenance of civil infrastructure (e.g., tunnels, overpasses, and buildings) is strenuous and fatigue-inducing for human workers and is particularly well-suited for co-robotization. Such work is typically quasi-repetitive, and on-site robots must adapt to unexpected workface conditions. Methods such as learning from demonstration can leverage human experts’ demonstration to let robots directly learn new skills to perform tasks. This paper proposes a generalized cylinders with orientation approach to teach robots how to perform quasi-repetitive overhead construction tasks from human demonstration. The demonstration trajectories are first used to construct a generalized cylinder and generate the robot trajectory. To ensure that the construction component (e.g., tunnel lining segment, building ceiling tile) being installed can satisfy the geometric constraints of the workspace, orientation constraints need to be determined, and the robot must follow such constraints. A trajectory adaptation and human-in-the-loop refinement approach are developed to refine the robot trajectory. The proposed method was evaluated in a robot simulator with variable workspace. The results showed that the proposed approach achieves an improved success rate (82.0%) compared to that demonstrated in previous work (71.3%) and enables overhead construction robots to readily adapt to new worksite conditions.

Selective Laser Melting of 304L and 316L Stainless Steels: A Comparative Study of Microstructures and Mechanical Properties

Among various types of stainless steel, 304L and 316L have the most engineering applications. Herein, 304L and 316L powders with similar size distributions and morphologies are used as raw materials for selective laser melting (SLM) using the same parameters. It is found that SLM 304L has two phases, γ‐austenite (≈95%) and δ‐ferrite (≈5%) phases, while SLM 316L contains only γ‐austenite phase. The average grain size is found to be 4.9 μm (average grain size of γ‐austenite phase: 5.0 μm; δ‐ferrite: 3.4 μm) for SLM 304L and 16.7 μm for SLM 316L. The small grain size of 304L is attributed to the peritectic reaction during solidification. δ‐ferrite acts as a heterogeneous nucleation site for γ‐austenite. SLM 316L has higher hardness and yield strength than 304L. Results obtained from the comparative study indicate that adding ferrite stabilizer elements (e.g., Cr, Mo, Si, Nb, or Ti) into 316L can lead to peritectic reaction or austenite to ferrite solid phase transformation, which is a possible approach for grain refinement.

Interface refinement of low- to medium-resolution Cryo-EM complexes using HADDOCK2.4

A wide range of cellular processes requires the formation of multimeric protein complexes. The rise of cryo-electron microscopy (cryo-EM) has enabled the structural characterization of these protein assemblies. The density maps produced can, however, still suffer from limited resolution, impeding the process of resolving structures at atomic resolution. In order to solve this issue, monomers can be fitted into low- to medium-resolution maps. Unfortunately, the models produced frequently contain atomic clashes at the protein-protein interfaces (PPIs), as intermolecular interactions are typically not considered during monomer fitting. Here, we present a refinement approach based on HADDOCK2.4 to remove intermolecular clashes and optimize PPIs. A dataset of 14 cryo-EM complexes was used to test eight protocols. The best-performing protocol, consisting of a semi-flexible simulated annealing refinement with centroid restraints on the monomers, was able to decrease intermolecular atomic clashes by 98% without significantly deteriorating the quality of the cryo-EM density fit.

Segregation of Atmospheric Oxidants in Turbulent Urban Environments

In the atmospheric boundary layer that is affected by turbulent motions and inhomogeneous surface chemical emissions, short-lived reactive species may not be completely mixed within any given airmass. Coarse atmospheric models, which assume complete mixing within each grid-box, may overestimate the rates at which chemical species react. We used a large eddy simulation (LES) model embedded in the Weather Research and Forecasting (WRF) model to assess the influence of species segregation on the photochemistry in the convective boundary layer. We implemented our model in the vicinity of Hong Kong Island, which is subject to strong turbulent flow and spatially inhomogeneous anthropogenic and biogenic emissions. We conclude that under heavy pollution conditions, segregation reduces the rate of the reaction between anthropogenic hydrocarbons and hydroxyl radical (OH) by 25% near the surface in urban areas. Furthermore, under polluted conditions, segregation reduces the ozone production rate in the urbanized areas by 50% at about 100 m above the surface. The reduction is only equal to 20% near the surface in the forested mountain area. This highlights the need to develop grid refinement approaches in regional and global models in the vicinity of large urban areas with high pollution levels. Under clean conditions, our large eddy simulations suggest that the role of segregation is small and can be ignored in regional and global modelling approaches.

Enhanced dielectric and ferroelectric responses in La3+/Ti4+ co-substituted SrBi2Ta2O9 Aurivillius phase

The molten salt technique was employed to prepare the Aurivillius phases SrBi2Ta2O9 (SBT) and Sr0.9La0.1Bi2Ta1.9Ti0.1O9 (SLBTT). The XRD data and the Le Bail refinement approach demonstrate that both samples formed the double-layer Aurivillius phase with the orthorhombic A21am structure successfully. The SLBTT cell volume is smaller compared to SBT with the substitution of smaller La3+ and Ti4+ ions and the increased size of the plate-like grains. FTIR analysis indicates the two local arrangements of Ti4+ at the B-site to form Ti–O–Ti and Ti–O–Ta bonds. Changes in the structural properties due to La3+ and Ti4+ substitution are reflected in the electrical properties. The higher ferroelectric transition temperature (Tc) of 455°C with the diffused phase transition behavior (DPT) was obtained in SLBTT. The unsaturated hysteresis loop of SLBTT obtained the ferroelectric remnant polarization (Pr) of 0.43 μC/cm2 and the coercive field (Ec) of 110.6 kV/cm, respectively. The enhanced ferroelectric characteristic as well as a higher bandgap (Eg) that is driven by the substitution of variable smaller cations.

Elucidation of the Bulging Effect by an Improved Ray‐Tracing Algorithm in Deep Penetration Wire Feed Laser Beam Welding and Its Influence on the Mixing Behavior

Herein, an improved ray‐tracing routine using a virtual mesh refinement approach is adopted in a 3D transient multiphysics computational fluid dynamics model for deep penetration wire feed laser beam welding. In a previous study, it was shown that the improved localization of the reflection points of the subrays within the keyhole leads to a more realistic development of the keyhole depth being validated with experimental results. Another effect investigated in detail herein is a drastic change in the flow behavior in the weld pool, which promotes the occurrence of a necking area in the solidification line and subsequent bulging under specific circumstances. This has a detrimental effect on the filler material element transport in the weld pool, leading to an inhomogeneous dilution of the added material. The numerical observations are backed up by experimentally obtained data, allowing to provide a clear physics‐based explanation of the reduced mixing behavior of the filler wire in the melt pool.

A hybrid adaptive multiresolution approach for the efficient simulation of reactive flows

Computational studies that use block-structured adaptive mesh refinement (AMR) approaches suffer from unnecessarily high mesh resolution in regions adjacent to important solution features. This deficiency limits the performance of AMR codes. In this work a novel hybrid adaptive multiresolution (HAMR) approach to AMR-based calculations is introduced to address this issue. The multiresolution (MR) smoothness indicators are used to identify regions of smoothness on the mesh where the computational cost of individual physics solvers may be decreased by replacing direct calculations with interpolation. We suggest an approach to balance the errors due to the adaptive discretization and the interpolation of physics quantities such that the overall accuracy of the HAMR solution is consistent with that of the MR-driven AMR solution. The performance of the HAMR scheme is evaluated for a range of test problems, from pure hydrodynamics to turbulent combustion.

Composite refinement techniques for solving linear systems

A composite refinement approach for stationary iterative methods is introduced. Two new formulas (RJGS and RGSJ) are compared with the classical forms. Rates of convergence of the introduced composite formulas (RJGS and RGSJ) are well established. The efficient performance of the new forms is established theoretically and confirmed through numerical examples. The decrease in the required number of iterations for convergence is established through the calculation of the spectral radius of the iteration matrices. The algorithmic structure of the new formulas is announced. Three numerical examples with different convergent properties are considered. The calculations are performed with the help of computer algebra software Mathematica.

Process development for advanced simulated moving bed (ASMB) chromatography by parameter refinement using pilot plant experimental data

The advanced simulated moving bed (ASMB) chromatography, which is a new operating strategy in the chromatography process, is proposed and a case study of design and process development is presented. The ASMB strategy divides the operation of the conventional simulated moving bed (SMB) carried out in a single step into five substeps. A detailed analysis based on simulation is carried out, which shows improvement in purity and recovery over the conventional SMB process. The model mismatch in the complex operations is resolved by a novel parameter estimation approach, where multiple data sets obtained from pilot plant experiments refine the model parameters. It was demonstrated in a separation case study of glucose and fructose that the proposed model refinement approach using 20 data sets from ASMB pilot plant experiments improves the prediction from the one obtained only through a single-column chromatography experiment. The refined model will be a powerful tool for the design and control of the ASMB process.