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ipie is a Python-based auxiliary-field quantum Monte Carlo (AFQMC) package that has undergone substantial improvements since its initial release [Malone et al., J. Chem. Theory Comput. 19(1), 109–121 (2023)]. This paper outlines the improved modularity and new capabilities implemented in ipie. We highlight the ease of incorporating different trial and walker types and the seamless integration of ipie with external libraries. We enable distributed Hamiltonian simulations of large systems that otherwise would not fit on a single central processing unit node or graphics processing unit (GPU) card. This development enabled us to compute the interaction energy of a benzene dimer with 84 electrons and 1512 orbitals with multi-GPUs. Using CUDA and cupy for NVIDIA GPUs, ipie supports GPU-accelerated multi-slater determinant trial wavefunctions [Huang et al. arXiv:2406.08314 (2024)] to enable efficient and highly accurate simulations of large-scale systems. This allows for near-exact ground state energies of multi-reference clusters, [Cu2O2]2+ and [Fe2S2(SCH3)4]2−. We also describe implementations of free projection AFQMC, finite temperature AFQMC, AFQMC for electron–phonon systems, and automatic differentiation in AFQMC for calculating physical properties. These advancements position ipie as a leading platform for AFQMC research in quantum chemistry, facilitating more complex and ambitious computational method development and their applications. [ABSTRACT FROM AUTHOR]

In molecular simulations, efficient methods for investigating equilibration and slow relaxation in dense systems are crucial yet challenging. This study focuses on the diffusional characteristics of monodisperse hard disk systems at equilibrium, comparing novel methodologies of event-chain Monte Carlo variants, specifically the Newtonian event-chain and straight event-chain algorithms. We systematically analyze both event-based and CPU time-based efficiency in liquid and solid phases, aiming to elucidate the microscopic mechanisms underlying structural relaxation. Our results demonstrate how chain length or duration, system size, and phase state influence the efficiency of diffusion dynamics, including hopping motion. This work provides insights into optimizing simulation techniques for highly packed systems and has the potential to improve our understanding of diffusion dynamics even in complex many-body systems. [ABSTRACT FROM AUTHOR]

Existing methods to compute theoretical spectra are restricted to the use of time-correlation functions evaluated from accurate atomistic molecular dynamics simulations, often at the ab initio level. The molecular interpretation of the computed spectra requires additional steps to deconvolve the spectroscopic contributions from local water and surface structural populations at the interface. The lack of a standard procedure to do this often hampers rationalization. To overcome these challenges, we rewrite the equations for spectra calculation into a sum of partial contributions from interfacial populations, weighted by their abundance at the interface. We show that SFG signatures from each population can be parameterized into a minimum dataset of reference partial spectra. Accurate spectra can then be predicted by just evaluating the statistics of interfacial populations, which can be done even with force field simulations as well as with analytic models. This approach broadens the range of simulation techniques from which theoretical spectra can be calculated, opening toward non-atomistic and Monte Carlo simulation approaches. Most notably, it allows constructing accurate theoretical spectra for interfacial conditions that cannot even be simulated, as we demonstrate for the pH-dependent SFG spectra of silica/water interfaces. [ABSTRACT FROM AUTHOR]

We perform large-scale atomistic simulations of a system containing 12 × 106 atoms, comprising an oxygen gas-filled bubble immersed in water, to understand the stability and cavitation induced by ultrasound. First, we propose a method to construct a bubble/water system. For a given bubble radius, the pressure inside the bubble is estimated using the Young–Laplace equation. Then, this pressure is used as a reference for a constant temperature, constant pressure simulation of an oxygen system, enabling us to extract a sphere of oxygen gas and place it into a cavity within an equilibrated water box. This ensures that the Young–Laplace equation is satisfied and the bubble is stable in water. Second, this stable bubble is used for ultrasound-induced cavitation simulations. We demonstrate that under weak ultrasound excitation, the bubble undergoes stable cavitation, revealing various fluid velocity patterns, including the first-order velocity field and microstreaming. These fluid patterns emerge around the bubble on a nanometer scale within a few nanoseconds, a phenomenon challenging to observe experimentally. With stronger ultrasound intensities, the bubble expands significantly and then collapses violently. The gas core of the collapsed bubble, measuring 3–4 nm, exhibits starfish shapes with temperatures around 1500 K and pressures around 6000 bar. The simulation results are compared with those from Rayleigh–Plesset equation modeling, showing good agreement. Our simulations provide insights into the stability and cavitation of nanosized bubbles. [ABSTRACT FROM AUTHOR]

Beyond hexagons, a distinctive family of pentagonal two-dimensional materials (2DMs) has emerged, featuring asymmetric geometry, exotic characteristics, and promising applications. Pentagonal tessellation of 2DMs generally leads to semiconducting bandgaps and directional electrical and optical properties. The theoretical prediction of penta-graphene and the experimental realization of materials, such as PdSe2, PdPSe, PdPS, and NiN2, have revealed a new horizon for penta-materials, showcasing high air stability and inherent auxeticity. Due to the rarity of pentagonal topology in nature, it is crucial to employ computational models and simulations to establish the stable configurations of these materials and understand their behavior in pentagonal arrangements. Consequently, the multitude of theoretically predicted penta-materials far surpasses the number of experimentally synthesized ones, numbering in the hundreds. A comprehensive catalog encapsulates recent progress, properties, and future perspectives, unlocking their full potential and paving the way for experimental realization. This review presents an extensive compilation of predicted penta-materials to date, elucidating their properties and potential applications. [ABSTRACT FROM AUTHOR]

Excessive monetary compensation and existing contractual agreements of influencers limit the ability of many firms to engage in effective influencer seeding. The authors suggest a forward-looking approach of targeting prospective influencers —while they are still largely unknown (e.g., a few months after their platform registration)—and signing them to endorse the firm in the future (e.g., more than a year later). This approach has the potential to significantly reduce costs. However, as only rarely do newly registered users ultimately become influencers (and as signals are weak), the authors propose a novel framework to cope with this rare-event problem. For empirical demonstration and application, the authors conduct data-based simulations using a data set from a worldwide leading audio platform. Every wave of newly registered users is associated with a profit potential stemming from future endorsements by prospective influencers. With knowledge about the order of magnitude of the return on successful influencer spend, managers applying the framework can extract around 20% of this profit potential (if the return is around three times the spend). [ABSTRACT FROM AUTHOR]

The robotic live-cube compact storage system can provide a higher storage capacity and more flexible throughput than other automated warehousing systems. The extant studies usually fix the input/output point at the bottom-left of such storage systems and have not investigated other configurations of the input/output point. In this study, we propose six policies for the configuration of the input/output point and evaluate their performance by using an analytical model and simulations. A sensitivity analysis is carried out by considering different shape-related factors, system heights, and energy consumption to explore the optimal configuration of the input/output point. For most input/output point policies, a shape factor (length divided by depth) of 0.5 results in good system performance in terms of retrieval time. When using optimal system dimension, the input/output point located in the upper-middle part along the length and depth performs best compared with other policies. Specifically, this configuration reduces the retrieval time by 40.23% and energy consumption by 42.31% compared with the bottom-left corner input/output point. We find that there exists a trade-off among the cost of setup, number of empty grids, and retrieval time when varying the number of input/output points. [ABSTRACT FROM AUTHOR]

We present an approximate semiclassical (SC) framework for mixed quantized dynamics in Wigner phase space in a two-part series. In the first article, we introduced the Adiabatic Hybrid Wigner Dynamics (AHWD) method that allows for a few important "system" degrees of freedom to be quantized using high-level double Herman–Kluk SC theory while describing the rest (the "bath") using classical-limit linearized SC theory. In this second article, we extend our hybrid Wigner dynamics to nonadiabatic processes. The resulting Nonadiabatic Hybrid Wigner Dynamics (NHWD) has two variants that differ in the choice of degrees of freedom to be quantized. Specifically, we introduce NHWD(E) where only the electronic state variables are quantized and the NHWD(V) where both electronic state variables and a handful of strongly coupled nuclear modes are quantized. We show that while NHWD(E) proves accurate for a wide range of scattering models and spin-boson models, systems where a few nuclear modes are strongly coupled to electronic states require NHWD(V) to accurately capture the long-time dynamics. Taken together, we show that AHWD and NHWD represent a new framework for SC simulations of high-dimensional systems with significant quantum effects. [ABSTRACT FROM AUTHOR]

A precise dynamical characterization of quantum impurity models with multiple interacting orbitals is challenging. In quantum Monte Carlo methods, this is embodied by sign problems. A dynamical sign problem makes it exponentially difficult to simulate long times. A multi-orbital sign problem generally results in a prohibitive computational cost for systems with multiple impurity degrees of freedom even in static equilibrium calculations. Here, we present a numerically exact inchworm method that simultaneously alleviates both sign problems, enabling simulation of multi-orbital systems directly in the equilibrium or nonequilibrium steady-state. The method combines ideas from the recently developed steady-state inchworm Monte Carlo framework [Erpenbeck et al., Phys. Rev. Lett. 130, 186301 (2023)] with other ideas from the equilibrium multi-orbital inchworm algorithm [Eidelstein et al., Phys. Rev. Lett. 124, 206405 (2020)]. We verify our method by comparison with analytical limits and numerical results from previous methods. [ABSTRACT FROM AUTHOR]

We describe a general-purpose computational toolkit for simulating open quantum systems, which provides numerically exact solutions for composites of zero-dimensional quantum systems that may be strongly coupled to multiple, quite general non-Markovian environments. It is based on process tensor matrix product operators (PT-MPOs), which efficiently encapsulate environment influences. The code features implementations of several PT-MPO algorithms, in particular Automated Compression of Environments for general environments comprised of independent modes as well as schemes for generalized spin boson models. The latter includes a divide-and-conquer scheme for periodic PT-MPOs, which enable million time step simulations for realistic models. PT-MPOs can be precalculated and reused for efficiently probing different time-dependent system Hamiltonians. They can also be stacked together and combined to provide numerically complete solutions of small networks of open quantum systems. The code is written in C++ and is fully controllable by configuration files, for which we have developed a versatile and compact human-readable format. [ABSTRACT FROM AUTHOR]

Here, we establish an approach to determine temperature-dependent aggregation rates in terms of thermostatistical quantities, which can be obtained directly from flat-histogram and statistical temperature algorithms considering the density of states of the system. Our approach is validated through simulations of an Ising-like model with anisotropically interacting particles at temperatures close to its first-order phase transition. Quantitative comparisons between the numerically obtained forward and reverse rates to approximate analytical expressions corroborate its use as a model-independent approach. [ABSTRACT FROM AUTHOR]

Clathrate hydrates are vital in energy research and environmental applications. Understanding their stability is crucial for harnessing their potential. In this work, we employ direct coexistence simulations to study finite-size effects in the determination of the three-phase equilibrium temperature (T3) for methane hydrates. Two popular water models, TIP4P/Ice and TIP4P/2005, are employed, exploring various system sizes by varying the number of molecules in the hydrate, liquid, and gas phases. The results reveal that finite-size effects play a crucial role in determining T3. The study includes nine configurations with varying system sizes, demonstrating that smaller systems, particularly those leading to stoichiometric conditions and bubble formation, may yield inaccurate T3 values. The emergence of methane bubbles within the liquid phase, observed in smaller configurations, significantly influences the behavior of the system and can lead to erroneous temperature estimations. Our findings reveal finite-size effects on the calculation of T3 by direct coexistence simulations and clarify the system size convergence for both models, shedding light on discrepancies found in the literature. The results contribute to a deeper understanding of the phase equilibrium of gas hydrates and offer valuable information for future research in this field. [ABSTRACT FROM AUTHOR]

For an e-hailing taxi operation, we analyse a driver's profit-maximising reactive strategy (to either accept or refuse a ride request) in response to the ride request broadcast by the platform. We analyse four operating modes, each of which is a combination of either of two reactive strategies: no refusal and refusal based on proximity, and either of two broadcasting methods. In an operating mode, our objective is to evaluate the expected total profit in a shift. We adopt a two-stage methodology to answer the research questions. In the first stage, we develop an agent-based simulation model to capture the effect of multiple taxis on driver's reactive strategy. Using real trip data, we find that a driver could follow a strategy of refusal based on proximity and earn approximately 25% more than the baseline no refusal strategy. In the second stage, we develop an approximate analytical model for a single taxi operation and compare the performance against the agent-based simulation model. We develop closed-form expressions of the expected total profit for each operating mode and topology of the service region. We find that our approximate analytical model provides an upper bound, and the profit deviation lies within 20% of the agent-based simulation model. [ABSTRACT FROM AUTHOR]

The adoption of simulation models as Digital Twins (DTs) has been standing out in recent years and represents a revolution in decision-making. In this context, we note increasingly faster and more efficient decisions by mirroring the behaviour of physical systems. On the other hand, we highlight the challenges to ensure the simulation models validity over time since traditional validation approaches have limitations when we consider the periodic update of the model. Thus, the present work proposes an approach based on the constant assessment of these models through Machine Learning and control charts. To this end, we suggest a monitoring tool using the K-Nearest Neighbors (K-NN) classifier, combined with a p-control chart, to periodically assess the validity of DT simulation models. The proposed approach was tested in several theoretical cases and also implemented in a real case study. The findings suggest that the proposed tool can monitor the DT functioning and identify possible special causes that could compromise its results. Finally, we highlight the wide applicability of the proposed tool, which can be used in different DT models, including near/real-time models with different characteristics regarding connection, integration, and complexity. [ABSTRACT FROM AUTHOR]

Our research strives to examine how simulation models of logistics systems can be produced automatically from verbal descriptions in natural language and how human experts and artificial intelligence (AI)-based systems can collaborate in the domain of simulation modelling. We demonstrate that a framework constructed upon the refined GPT-3 Codex is capable of generating functionally valid simulations for queuing and inventory management systems when provided with a verbal explanation. As a result, the language model could produce simulation models for inventory and process control. These results, along with the rapid improvement of language models, enable a significant simplification of simulation model development. Our study offers guidelines and a design of a natural language processing-based framework on how to build simulation models of logistics systems automatically, given the verbal description. In generalised terms, our work offers a technological underpinning of human-AI collaboration for the development of simulation models. [ABSTRACT FROM AUTHOR]

The article discusses the appropriateness of using simulations in academic research, questioning when simulations are the right tools for theorizing but emphasizing their suitability when data are unavailable or mathematical models are intractable. Using an example that models entrepreneurial lean-startup philosophy the author focuses on a specific simulation-based study by Chen, Elfenbein, Posen, and Wang, which explores the optimization of experiments and pivoting in entrepreneurial decision-making. Several omissions and limitations in the simulation are highlighted, including the lack of consideration for competition, the oversimplified representation of upside optionality, the absence of heterogeneity in experiments and pivots, and the neglect of endogeneity in the experimentation period. The article concludes by urging researchers to justify the use of simulations and apply them more carefully, considering their relative strengths and potential limitations.

Owing to increasingly important drivers for change, such as automation, digitisation, and dynamic demand patterns, simulation models of production systems become outdated rapidly. At the same time, building simulation models often requires much time, cost, and expertise, especially when dealing with complex job shop production systems. To address these challenges, an automated simulation model generation (ASMG) framework for material flow simulation of production systems is presented. This framework contains multiple approaches to infer routeing, control and temporal aspects from event-based data. To achieve this, methods from process mining (PM) and machine learning (ML) are applied. Additionally, the suitability of Coloured Petri Nets (CPNs) to serve as conceptual and operational simulation models is examined. The inferred simulation models have high validity when compared to the real system concerning the KPIs machine utilisation, throughput, and work in process. It is shown, that most model elements can be inferred very well, in particular process routes, processing times, and resource selection rules. This proof of concept serves as a foundation for research on detection approaches inferring further model elements such as setup times accurately. [ABSTRACT FROM AUTHOR]

We introduce a simple cutoff-based method for precise electrostatic energy calculations in the molecular dynamics (MD) simulations of point-particle systems. Our method employs a theoretically derived smooth pair potential function to define electrostatic energy, offering stability and computational efficiency in MD simulations. Instead of imposing specific physical conditions, such as dielectric environments or charge neutrality, we focus on the relationship represented by a single summation formula of charge-weighted pair potentials. This approach allows an accurate energy approximation for each particle, enabling a straightforward error analysis. The resulting particle-dependent pair potential captures the charge distribution information, making it suitable for heterogeneous systems and ensuring an enhanced accuracy through distant information inclusion. Numerical investigations of the Madelung constants of crystalline systems validate the method's accuracy. [ABSTRACT FROM AUTHOR]

Despite the enormous theoretical and application interests, a fundamental understanding of the glassy dynamics remains elusive. The static properties of glassy and ordinary liquids are similar, but their dynamics are dramatically different. What leads to this difference is the central puzzle of the field. Even the primary defining glassy characteristics, their implications, and if they are related to a single mechanism remain unclear. This lack of clarity is a severe hindrance to theoretical progress. Here, we combine analytical arguments and simulations of various systems in different dimensions and address these questions. Our results suggest that the myriad of glassy features are manifestations of two distinct mechanisms. Particle caging controls the mean, and coexisting slow- and fast-moving regions govern the distribution of particle displacements. All the other glassy characteristics are manifestations of these two mechanisms; thus, the Fickian yet non-Gaussian nature of glassy liquids is not surprising. We discover a crossover, from stretched exponential to a power law, in the behavior of the overlap function. This crossover is prominent in simulation data and forms the basis of our analyses. Our results have crucial implications on how the glassy dynamics data are analyzed, challenge some recent suggestions on the mechanisms governing glassy dynamics, and impose strict constraints that a correct theory of glasses must have. [ABSTRACT FROM AUTHOR]

Accurate Force Fields (FFs) are essential for Molecular Dynamics (MD) simulations of the dynamics of realistic materials in terms of atomic-level interactions. The FF parameters of short-range valence interactions can be derived through Quantum Mechanical (QM) calculations on model systems practical for QM (<300 atoms). Similarly, the dynamic electrostatic interactions can be described with methods such as QEq or PQEq that allow charges and polarization to adjust dynamically. However, accurately extracting long-range van der Waals (vdW) interactions from QM calculations poses challenges due to the absence of a definitive method to distinguish between the different energetic components of electrostatics, polarization, vdW, hydrogen bonding, and valence interactions. To do this we use the Perdew–Burke–Ernzerhof flavor of Density Functional Theory, including empirical D3 vdW corrections, to predict the Equation of State for each element (keeping any covalent bonds fixed), from which we obtain the two-body vdW nonbond potential. Here, we extend these calculations to include non-bonded parameters for the N and O columns of the periodic table so that we now describe columns 15 (N), 16 (O), 17 (F), and 18 (Ne) of the periodic table. For these 20 elements, we find that the two-body vdW potentials can all be mapped to a single universal two-body curve, with just three scaling parameters: Re, De, and L. We refer to this as the Universal NonBond (UNB) potential. We expect this to be useful for new MD simulations and a helpful starting point to obtain UNB parameters for the remainder of the periodic table. [ABSTRACT FROM AUTHOR]

Barkhausen noise is a type of magnetic noise that occurs due to the interaction of domain walls with defects. In magnetic sensor applications, this can be a detrimental phenomenon since it disturbs the signal. We study this noise using coupled micro-magneto-mechanical finite element simulations. To this end, we consider in the first step a thermodynamically consistent material model within the generalized standard material approach. In our material model, we include exchange, anisotropy, demagnetizing, Zeeman, and elastic energy. The coupling between mechanics and micro-magnetics is implemented via a magnetostrictive strain contribution. In the following step, we extend the material model to represent the full Landau–Lifschitz–Gilbert magnetization dynamics. For the model extension, we give a detailed exposition of the finite element implementation. In particular, we use a new modified leapfrog/Crank–Nicolson time integration scheme, which preserves the magnetization magnitude exactly. Furthermore, we showcase in detail the scheme for applying our material model to noise computation (based on ensemble averaging). Finally, we investigate various numerical examples based on the magnetostrictive material FeCoSiB to illustrate the different features of our approach. [ABSTRACT FROM AUTHOR]

The complexity and variability of the structural distribution and combination characteristics of jointed rock masses make the response mechanism of tunnel rock collapse different, and there is a lack of systematic research on the existing perimeter rock instability mode and bolt support scheme. Based on numerical simulations of the block system structure of a nodular rock mass, the existing theory of bolt support is compared and analyzed to explore the scope of their respective applications. Combined with the spatial and temporal transport law of block instability, a new batch instability model of jointed rock tunnels is proposed, which reveals the progressive collapse catastrophe evolution mechanism of a collapsed interlocking block system after the instability of the key blocks and elucidates the coupling mechanism between the bolts and the block system structure as well as their anchoring effectiveness. Finally, for the actual tunnel project, the instability batches of the surrounding rock are identified, and the corresponding optimized design of the bolt support is presented, which has achieved good support effects. The research results can provide important theoretical guidance and practical engineering value for risk avoidance, disaster identification and targeted prevention and control of dangerous rock fall and chain collapse instability disasters in jointed rock body tunnels. [ABSTRACT FROM AUTHOR]

From the external perspective of digital technology diffusion in regional innovation ecosystems, this study divides innovation promotion into information dissemination and precision subsidy promotion strategies, and uses multi-agent modelling and simulation method to analyse the impact of innovation promotion strategies on digital technology diffusion in regional innovation ecosystems. The results are as follows. (1) The diffusion rate and depth of digital technology in regional innovation ecosystems with an information dissemination promotion strategy are better than those without this strategy. Early, high-strength centralised promotion strategy has the highest rate and depth of digital technology diffusion, and implementing distributed information promotion strategy in the late stage can maximise the rate and depth of digital technology diffusion. (2) When the number of target enterprises is insufficient, the precision subsidy promotion strategy cannot achieve the desired effect. With an increase in the number of target enterprises, the diffusion rate and depth of digital technology in regional innovation ecosystems gradually increased and showed a classic ‘S’-type diffusion curve. By focusing on the overall trend, the average rate and depth of digital technology diffusion in regional innovation ecosystems with a relationship embeddedness strategy are the best. [ABSTRACT FROM AUTHOR]

Background: A time-dependent analysis, usually by means of Poisson and Cox regression models, can be applied to prevent immortal time bias. However, the use of the Poisson model requires the assumption that the event rate is constant over time. This study aims to assess the potential consequences of using the Poisson model to cope with immortal time bias on estimating the exposure-outcome relationship in the case of time-varying risks. Methods: A simulation study was carried out. Survival times were assumed to follow a Weibull distribution, and the Weibull parameters were chosen to identify three different scenarios: the hazard of the event is constant, decreases, or increases over time. A dichotomous time-varying exposure in which patients can change at most once from unexposed to exposed was considered. The Poisson model was fitted to estimate the exposure-outcome association. Results: Small changes in the outcome risk over time (as denoted by the shape parameter of the Weibull distribution) strongly affected the exposure-outcome association estimate. The estimated effect of exposure was always lower and greater than the true exposure effect when the event risk decreases or increases over time, and this was the case irrespective of the true exposure effect. The bias magnitude was positively associated with the prevalence of and time to exposure. Conclusions: Biased estimates were obtained from the Poisson model to cope with immortal time. In settings with a time-varying outcome risk, the model should adjust for the trend in outcome risk. Otherwise, other models should be considered. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, the Smoothed Particle Hydrodynamics method is used to simulate the dynamic response of the floating offshore wind turbine mooring system in a complex marine environment by using its advantages of dealing with free surface flow and fluid–structure interaction. The single‐cable mooring system and the double‐cable mooring system are introduced into the numerical simulation model of fluid–solid coupling interaction. The first‐order irregular wave and the second‐order regular wave are used to simulate different wave conditions. The operating state of the platform in these two cases is analyzed, and the accurate data such as the velocity change of the geometric center of the platform and the change of six degrees of freedom are obtained. Using visual processing and data analysis, it is found that the optimized double‐cable mooring system structure improves the vibration reduction ability of the platform. [ABSTRACT FROM AUTHOR]

ABSTRACT To address the issue of significant loss increase in planar transformers at high frequencies in LLC resonant converters, the winding width of the transformer was optimized. This design minimizes losses due to eddy currents and skin effects, thereby optimizing the transmission efficiency of the LLC resonant converter. This paper developed a mathematical model of the transformer windings, analyzed the losses in the windings and the core of the planar transformer, and summarized the design rules for three commonly used winding geometries. By determining the optimal winding width, the transformer losses were optimized. Using the finite element simulation software Maxwell3D, a 3D simulation model of the transformer was constructed. The simulation results were compared, and a 500‐W full‐bridge LLC prototype was built to validate the principles summarized in the paper. [ABSTRACT FROM AUTHOR]

Textile composites are advanced materials composed of preforms combined with matrix materials. The fiber structure in the preform has a significant impact on the mechanical properties of the composite. Precise control over preform dimensions and internal fiber structural uniformity, termed 'accurate shape control', is essential to ensure reliable and stable composite component mechanical properties. This paper reviews current research progress on fabric deformation mechanisms, focusing on experimental characterization and numerical simulation. Experimental methods for fabric deformation include tensile, compression, bending, and shear deformation, whereas numerical methods encompass macroscopic continuum, discrete, and semi‐discrete models. The insights offered in this paper will aid a greater understanding of fabric deformation mechanisms, enabling an accurate prediction of complex shape molding and effective process parameter design, ultimately facilitating the structural design and engineering applications of textile composites. Highlights: Recent trends and challenges in the study of fabric deformation mechanisms are presented.The experimental methods for fabric deformation were summarized and evaluated.Representative numerical modeling techniques and simulation methods are discussed.Some recommendations on potential future research directions are detailed. [ABSTRACT FROM AUTHOR]

Periodical cicadas are remarkable for their incredibly long, prime-numbered life cycles and almost perfectly synchronized mass emergence. Synchronized emergence is a generally localized event, referred to as a "brood". Broods are separated in space and time, or parapatric; adjacent broods emerge on different schedules, whereas some cicadas emerge off schedule, called stragglers. Straggling can potentially erode brood boundaries; thus, the mechanism allowing broods to maintain nonoverlapping distributions is highly puzzling. Here, we propose that predation may allow broods to exclude each other. Our model and numerical simulations show that predation could act as an important factor for maintaining the nonoverlapping distributions. The proposed mechanism is most effective in the vicinity of the critical strength of predation, beyond which the population is doomed to extinction. An increase in predation intensity increases resistance to settlement of a minority brood, while suppressing the main brood population. [ABSTRACT FROM AUTHOR]

Noisy intermediate-scale quantum (NISQ) computers provide a new experimental platform for investigating the behaviour of complex quantum systems. We show that currently available NISQ devices can be used for versatile quantum simulations of chaotic systems. We introduce a classical-quantum hybrid approach for exploring the dynamics of the chaotic quantum kicked top (QKT) on a quantum computer. The programmability of this approach allows us to experimentally explore a broad range of QKT chaoticity parameter regimes inaccessible to previous studies. Furthermore, the number of gates in our simulation does not increase with the number of kicks, thus making it possible to study the QKT evolution for arbitrary number of kicks without fidelity loss. Using a publicly accessible NISQ computer (IBMQ), we observe periodicities in the evolution of the 2-qubit QKT, as well as signatures of chaos in the time-averaged 2-qubit entanglement. We also demonstrate a connection between entanglement and delocalization in the 2-qubit QKT, confirming theoretical predictions. [ABSTRACT FROM AUTHOR]

ABSTRACT With shortening development cycles, digital development rises in importance. Therefore, we present an approach to segment digital carlines based on their corrosion risk using digital data sets. A typical carline is described via STL‐Files that accumulate to approximately 25 million triangles. While physics‐based simulation models exist capable of predicting the onset of corrosion in local geometry settings, an application to a complex surface mesh would be prohibitively expensive to compute. This calls for data reduction techniques that reduce the number of triangles by identifying areas prone to corrosion, as well as those that are protected by measures such as adhesives. Therefore, the implementation of corrosion‐prone areas of a body‐in‐white part, as presented in Waibel et al., is extended by implementing a design measure segmentation for adhesive pipes. This work introduces a method to predict corrosion‐protected areas for flanges with adhesives by implementing a feature extraction and a transfer learning‐based workflow for data‐efficient training. The results of the implementation are the validated prediction on body‐in‐white parts with high precision. [ABSTRACT FROM AUTHOR]

In Tulving's initial characterization, episodic memory was one of multiple memory systems. It was postulated, in pursuit of explanatory depth, as displaying proprietary operations, representations and substrates such as to explain a range of cognitive, behavioural and experiential phenomena. Yet the subsequent development of this research programme has, paradoxically, introduced surprising doubts about the nature, and indeed existence, of episodic memory. On dominant versions of the 'common system' view, on which a single simulation system underlies both remembering and imagining, there are no processes unique to memory to support robust generalizations with inductive potential. Eliminativism about episodic memory seems to follow from the claim that it has no dedicated neurocognitive system of its own. After identifying this under-noticed threat, we push back against modern eliminativists by surveying recent evidence that still indicates specialized mechanisms, computations and representations that are distinctly mnemic in character. We argue that contemporary realists about episodic memory can retain lessons of the common system approach while resisting the further move to eliminativism. This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'. [ABSTRACT FROM AUTHOR]

The formation of ordered structures by Janus-like particles, composed of two parts (A and B), with orientation-dependent interactions on a triangular lattice was studied using Monte Carlo methods. The assumed lattice model allows each particle to take on one of the six orientations. The interaction between the A parts of neighboring particles was assumed to be attractive, while the AB and BB interactions were assumed to be repulsive. Moreover, it was assumed that the interaction between a pair of neighboring particles depended on the degrees to which their AA, AB, and BB parts face each other. It was shown that several ordered phases of different densities and structures may appear, depending on the magnitudes of AB and BB interactions. In particular, we found several structures composed of small clusters consisting of three ( O T ), four ( O R ), and seven (S) particles, surrounded by empty sites, the lamellar phases ( O L , O L 1 , and O L 3 ), the structures with hexagonal symmetry ( R 3 × 3 and K), as well as the structures with more complex symmetry ( R 5 × 5 and L A D) . Several phase diagrams were evaluated, which demonstrated that the stability regions of different ordered phases are primarily determined by the strengths of repulsive AB and BB interactions. [ABSTRACT FROM AUTHOR]

Building heating, ventilation, and air conditioning (HVAC) systems are affected by several errors that can cause thermal discomfort to occupants and waste energy in buildings. Therefore, early and accurate Fault Detection and Diagnosis (FDD) is vital for enhancing the system's efficiency. Data-driven FDD is promising because it is convenient compared to the first-principles-based rule set that demands in-depth expertise. However, to realize data-driven FDD for real-life cases, the data-imbalance problem in FDD must be solved. In this study, the authors suggest a novel approach that generates synthetic data from a building system simulation tool, HVACsim+, using them as a source model to apply transfer learning to a target air handling unit system. Even though from the existing target system only the normal operational data were available, the transfer learning approach was satisfactory, confirming that the proposed method effectively mitigates data imbalance in developing data-driven FDD. [ABSTRACT FROM AUTHOR]

Reliable hydrological simulations require accurate precipitation data. However, data uncertainties due to the indirect nature of satellite estimates can propagate through hydrological models and lead to simulation errors. This study assesses the accuracy of Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) products, comparing them directly with ground-based precipitation data and evaluating their performance in rainfall–runoff modelling across Great Britain. Three IMERG V06 products (IMERG-Early, IMERG-Late, and IMERG-Final) are examined. Utilizing the simple water balance model (SWBM), the analysis covers 250 basins, revealing that the SWBM performs well in over 50% of the basins. Runoff estimations show that European Observation (E-OBS) ground-based data yield the highest Nash-Sutcliffe efficiency (NSE) score (0.91), followed by IMERG-Final (0.85), IMERG-Late (0.82), and IMERG-Early (0.73). The findings underscore IMERG's utility in hydrological modelling for ungauged or poorly gauged basins. [ABSTRACT FROM AUTHOR]

Aiming at the problem caused by the fact that traditional on-board charging systems (OBC) usually use a single form of AC input, this research suggests a suitable isolated OBC for single-phase and three-phase power sources. It adopts a two-stage structure. The front stage can switch between different input modes. Using a single-phase AC input mode, the front stage is a totem pole bridgeless cascade Boost circuit for power factor correction (PFC). It can be switched to a three-phase six-switch PFC circuit in a three-phase AC input mode. A full-bridge LLC resonant converter serves as the rear stage. The system adopts a double closed-loop control strategy and a mixed control mode that consists of pulse width modulation (PWM) and pulse frequency modulation (PFM). In either the single-phase or three-phase AC input mode, the front stage PFC circuit can output a 700 V DC bus voltage, and keep the input current and input voltage in phase. It is possible to achieve soft switching in the rear stage resonant converter, and to output a wide range of voltage to charge the power battery. According to a theoretical analysis, a system simulation model is built and an experimental prototype of the OBC is produced. The accuracies of the simulation and the theoretical analysis are confirmed by experimental findings. [ABSTRACT FROM AUTHOR]

Objectives: Fluoroscopic guided procedures are a mainstay for interventional radiology (IR) procedures. Practice is needed for the novice to interpret fluoroscopic images and simultaneously perform the procedure hands-on as well as control the foot pedal to screen. We describe the development of a training simulation model which simulates the human kidney, ureter, and bladder. Methods: Stereolithography (SLA) 3D print technology using SLA resin and Anycubic SLA printer were employed. A plastic tubing was used to connect the 3D printed kidney and bladder as the ureter. This simulation model permits fluoroscopic guided filling of "pelvicalyceal system" with contrast as well as ureteric stenting, guidewire, and drainage catheter manipulation. Effectiveness of the model to attain skills for nephrostomy exchange and ureteric stenting was obtained via questionnaire from trainees prior to and after utilizing the model. Results: The 3D printing simulation model of the kidney, ureter, and bladder system enables trainees to perform nephrostomy exchange, nephrostogram, and antegrade stenting. Participants felt more confident to perform the procedures as they were more familiar with the procedure. Besides that, participants felt their wire and catheter manipulation skills have improved after using the simulation model. Conclusions: Neph-ex simulation model is safe and effective for hands-on training in improving proficiency of fluoroscopy-guided nephrostomy exchange and antegrade ureteric stenting. Advances in knowledge: As of our knowledge, there are no commercially available simulation models for fluoroscopic guided nephrostomy exchange and ureteric stent deployment. No article on nephrostomy exchange simulation model has been published before. [ABSTRACT FROM AUTHOR]

Summary: In wireless power transfer (WPT) systems, extended transmission distances significantly impede efficiency, posing a major challenge to their practical application. This paper presents a novel ortho‐octagonal double‐helix metamaterial that can effectively enhance the transmission efficiency of WPT systems. It has theoretically derived and experimentally verified the enhancement of evanescent wave transmission by this metamaterial dielectric plate. A WPT simulation system operating at 10.78 MHz is constructed by HFSS software, and the effects of adding passive relay coils and different shapes of metamaterials on the transmission efficiency are comparatively investigated. Simulated data converge to indicate that integrating variously shaped metamaterials at the transceiver's end distinctly elevates the WPT system's transmission efficiency. When the transceiver coil spacing of the WPT system is greater than 22 cm, the effect of metamaterials on the system transmission efficiency enhancement shows an increasing and then decreasing trend as the distance increases. The positive octagonal metamaterial improves 12% over the circular metamaterial in the mid‐range transmission distance due to its better magnetic coupling effect. When the transceiver coil spacing is 22 cm, the open‐circuit voltage of the receiving coil after loading the metamaterial is stabilized to be enhanced by nearly five times, and it has the best effect at 30 cm, and the transmission efficiency is enhanced from 30% to 60%, which verifies the effective enhancement of the metamaterial on the transmission efficiency of the WPT system. [ABSTRACT FROM AUTHOR]

Objective: To determine the individual learning curves for cordocentesis in a low‐cost simulator for maternal‐fetal medicine (MFM) fellows. Methods: This observational, descriptive, educational, and prospective study was performed from July through November 2022. After an introductory course based on a standardized technique for cordocentesis, each second‐year MFM fellow who accepted to participate in the study performed this procedure using a low‐cost simulation model, and experienced operators supervised the cordocenteses. Learning curves were then created using cumulative sum analysis (CUSUM). Results: Seven second‐year MFM fellows with no previous experience in cordocentesis accepted to participate in the study. A total of 2676 procedures were assessed. On average, residents performed 382 ± 70 procedures. The mean number of procedures to achieve proficiency was 369 ± 70, the overall success rate was 84.16%, and the corresponding failure rate was 15.84%. At the end of the study, all fellows were considered competent in cordocentesis. One fellow required 466 attempts to achieve competency, performing a total of 478 procedures, but the resident with the fewest attempts to reach competency required 219 procedures, completing 232 procedures. Some of the most frequent reasons for failed attempts included not reaching the indicated point for vascular access (20.99%) and being unable to retrieve the sample (69.10%). Conclusion: CUSUM analysis to assess learning curves, in addition to using low‐cost simulation models, helped to appraise individualized learning, allowing an objective demonstration of competency for cordocentesis among MFM fellows. Synopsis: Using a low‐cost simulation model, cumulative sum analysis was used to determine individual learning curves for cordocentesis among maternal‐fetal medicine fellows. [ABSTRACT FROM AUTHOR]

The critical role of latent heating (LH) in atmospheric blocking events is well-recognized, yet its influence on the predictability of such events remains underexplored. This study examines the prediction accuracy of winter atmospheric blocking days over the Northern Hemisphere, utilizing 20 years of retrospective forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF). Atmospheric blocking events are categorized into three sectors: Atlantic, Continent, and Pacific. Results indicate substantial variations in the LH contribution among different blocking events. During the first 21 days, the Pacific blockings exhibit the most significant impact on prediction skill under strong LH conditions, followed by the Continent blockings, with the Atlantic blockings being least affected. Interestingly, a consistent pattern emerged across sectors: blocking prediction skill is lower under strong LH than under weak LH. During the first 12 days, the Pacific sector typically exhibit lower prediction skill for blocking onset under strong LH, compared to weak LH. For blocking decay, a consistent pattern is observed: lower prediction skill under strong LH than weak LH. Regarding blocking intensity, the forecasting bias escalates with increasing lead time, particularly for strong LH. This study highlights the need to improve moist process simulations in models, aiming to improve atmospheric blocking forecasting accuracy. [ABSTRACT FROM AUTHOR]

This study compares the accuracy, efficiency, and reliability of variance reduction (VR) methods for Monte Carlo radiation transport simulations involving wide-area ground plane (i.e., "surface") and buried (i.e., "volumetric") gamma source emissions from environmental soil. The simulation models are idealized external exposure scenarios intended as a basis for deriving site-specific dose-based or carcinogenic risk–based regulatory limits in the radiological site remediation process. These simulations are computationally resource intensive since particle tracks are transported from an extremely large source region to a relatively small detector region. For each simulation, several VR methods are compared with metrics of accuracy, efficiency, and reliability. The MCNP deterministic transport (DXTRAN) VR method was most effective for problems involving sources emitting low-energy gamma rays, and a coupled multicode method was more effective for problems involving sources emitting higher-energy gamma rays that undergo significant attenuation in the soil. [ABSTRACT FROM AUTHOR]

In order to avoid the influence of external environmental factors on athletes' physical fitness and technical tactics, the author proposes the design and research of an integrated simulation training system for athletes' physical fitness and technical tactics based on virtual reality. The hardware unit of the design system includes a 3D scanner module, VR glasses module, locator module, tracker module, and wireless transceiver device. The software module introduces virtual reality technology and designs a visual simulation module, trained object detection module, trained object tracking module, and overall control module. The simulation experiment results show that compared with existing systems, the training scene output clarity and frame rate of the designed system are better, and the thread switching time and signal mixing time are shorter, which fully proves that the designed system has higher operating efficiency and better application performance. [ABSTRACT FROM AUTHOR]

CO2 flooding is an effective technology for suppling condensate gas reservoir pressure and mitigating global warming. In this study, numerical simulation studies have been conducted to enhance gas recovery in Pen5 condensate gas reservoir using CO2 flooding. Pen5 reservoir has lasted 20 years of primary depletion, which affected by water invasion and retrograde condensation. In numerical simulation study, the GEM module is applied to implement history‐matching of production data, and good agreement has been achieved. Based on comprehensive geological understanding, production dynamics, and numerical simulation techniques, areas with minimal impact from water invasion and retrograde condensation contamination have been delineated. The comparison between continued depletion and the implementation of CO2 injection as a replacement technology in favorable areas has demonstrated the feasibility of CO2 flooding development in these regions. The analysis of the advantages and disadvantages of using miscible flooding and immiscible flooding was conducted, and the optimal development well pattern was evaluated. In the end, the plan of CO2 flooding of Pen5 reservoir has been designed and the gas production rate in the next 10 years has been predicted. The research findings of this study have reference significance for the practical application of CO2 flooding in developing condensate gas reservoirs. [ABSTRACT FROM AUTHOR]

Real‐time hybrid simulation (RTHS) technique significantly streamlines experimental procedures by allowing researchers to study a substantial portion of the structure through numerical analysis. For effective real‐time interconnectivity between the investigated substructures, the numerical component must be solved within an extremely tight time frame. However, achieving a real‐time solution for large numerical substructures presents a major challenge. Hence, this paper proposes the Proper Orthogonal Decomposition (POD) method to reduce computational burden in RTHS and shows its implementation. The merits of the approach are shown by comparisons between the full‐order and reduced‐order numerical substructures, including nonlinearities. A shear frame retrofitted with superelastic shape memory alloy dampers is investigated as a numerical model. The soil‐structure interaction is also included using a finite element half‐space model with an artificial viscous‐spring boundary. Furthermore, the numerical substructure is coupled with shaking table experiments of a tuned liquid column damper to prove the feasibility of the method. With POD, the studied nonlinear numerical substructure can simulate up to 2655 degrees‐of‐freedom (DOFs) with a given hardware setup, while the full‐order model is limited to 135 DOF, underscoring the significance of the POD method in RTHS. [ABSTRACT FROM AUTHOR]

Interest in the phase behavior of hydrocarbons in shale reservoirs has grown in recent years. Petroleum fluid phase behavior has been observed to differ significantly between conventional reservoirs and shale reservoirs. Within shale reservoirs, notable surface-fluid interactions can lead to non-uniform molecule distribution and an alteration in fluid phase behavior, primarily caused by the existence of nano-scale porous materials. In this work, we study the phase behavior of methane in single cylindrical pore models. We apply the gauge Gibbs ensemble Monte Carlo (gauge-GEMC) simulation technique to investigate the phase behavior of methane in 4–10 nm single nanopores and calculate the saturation pressures at various temperatures using the grand canonical Monte Carlo (GCMC) simulation technique. A shift in the phase diagram has been found for methane in nanopores. As pore size decreases, the shift becomes more significant. [ABSTRACT FROM AUTHOR]

AbstractThe aim of this contribution is to propose new flexible spatial models based on a class of generalized sinh transformations. Our proposal greatly extends the Gaussian random field mainly in terms of asymmetry, heavy tail behavior, and bimodality. We demonstrate that we obtain a valid random field. We ensure that it is mean square continuous. We derive explicit expressions for the moments, the covariance function, the skewness, and the kurtosis of the random fields. In comparison with the available skew-Gaussian models, the proposed models could capture a greater amount of skewness and also accommodate clustered spatial outliers. The proposed models are computationally very tractable within the Bayesian framework here adopted. They are compared with the Gaussian and skew-Gaussian spatial models through simulation studies and an application to the spatial prediction of weekly rainfall near Darwin, Australia. The result suggests that the predictive performance in terms of different criteria under our method tends to be smaller than those obtained from the competing ones. [ABSTRACT FROM AUTHOR]

During the five-axis flank milling process, the uncut chip area varies continuously with the cutter motion, which leads to a challenging issue for the geometric construction of the instantaneous uncut chip thickness (IUCT). In this paper, a novel approach to calculate the IUCT effectively considering the cutter runout effect is proposed. The element motion of the cutter extracted from the cutter location file (CLF) is described with one linear variable and two angular variables, which are necessary factors in the IUCT calculation of five-axis milling. The geometry relationship between cutter motion and IUCT has been analyzed, and the parametric expression of IUCT in five-axis milling can be deduced to predict the cutting force. The explicit five-axis IUCT expression facilitates a more comprehensive understanding of the key parameters in the cutting process, which could be helpful in optimizing the processing parameters. Compared to the numerical method based on true tooth trajectories, the time consumption of the proposed method is reduced greatly in the simulation. The experiment of five-axis flank milling is carried out, and the result reveals that the presented method can be well applied to the practical milling process. We believe that the IUCT model in this paper will promote the simulation and optimization system in five-axis machining. [ABSTRACT FROM AUTHOR]

In this paper, we consider the spatiotemporal dynamics behaviors of a Leslie–Gower diffusion predator–prey system with prey refuge and Beddington–DeAnglis (B‐D) functional response. By using the Poincaré inequality and topological degree theory, we first investigate the Turing instability of the reaction–diffusion system and prove the existence of nonconstant positive steady‐state solutions. Then we discuss the steady‐state bifurcation and the direction to Hopf bifurcation of the PDE model by the local bifurcation theorem and center manifold theory. Finally, some numerical simulations are presented to supplement the analytic results in one dimension which indicates that changes in prey refuge and diffusion coefficient can increase the complexity of the system. [ABSTRACT FROM AUTHOR]

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AbstractModel checking evaluates the appropriateness of a statistical model based on the observed data, and it is essential to make valid statistical analyses. In this paper, a new procedure for model checking type II censored data is proposed. This procedure combines the Kullback-Leibler divergence, the Dirichlet process, and the relative belief ratio. The method is implemented via a computational algorithm and is explained through several examples. [ABSTRACT FROM AUTHOR]