Some distribution networks are characterized by weak grid structures and complex feeder deployment, which leads to missing information such as line parameters. Existing power flow methods depend heavily on accurate parameters and lack sufficient dyna...
Seismic multi-parameter full-waveform inversion (FWI) integrating velocity and density parameters can fully use the kinematic and dynamic information of observed data to reconstruct underground models. However, seismic multi-parameter FWI is a highly...
The increased usage of cyber-physical systems (CPS) has gained the focus of cybercriminals, particularly with the involvement of the internet, provoking an increased attack surface. The increased usage of these systems generates heavy data flows, whi...
With the continuous expansion of system scale, the parameter coupling of the system is prominent. Due to limitations in knowledge and experience, it is difficult for designers to objectively analyze the interaction relationship between parameters, re...
During hydraulic fracturing, expansion of internal micro-fractures deforms the rock to different extents. Numerical studies typically assume fixed parameters; however, in the field site, parameters are likely to vary. Error accumulation underlies dev...
The growing deployment of renewable energy systems calls for accurate parameter estimation and compact modeling of grid-connected inverter systems (GCISs). This paper presents a framework for parameter estimation and physics-structured model compress...
Accurate identification of hydrodynamic parameters is essential for high-fidelity modeling and control of unmanned underwater vehicles (UUVs). Compared with towing tank experiments and computational fluid dynamics simulations, system identification b...
As renewable penetration increases, the inertia, damping, and primary frequency regulation characteristics of renewable-rich power systems become strongly time-varying, making fixed offline frequency response models increasingly difficult to maintain...
Artificial neural networks have changed many fields by giving scientists a strong way to model complex phenomena. They are also becoming increasingly useful for solving various difficult scientific problems. Still, people keep trying to find faster a...
The study of the evolution law of basic physical parameters and dynamic compression performance of deep granite under the environment of the heating-cooling cycle is of great significance for the stability evaluation of deep underground engineering a...
Power grid parameter estimation involves the estimation of unknown parameters, such as the inertia and damping coefficients, from the observed dynamics. In this work, we present physics-informed machine learning algorithms for the power system parame...
In the operations of the banana postharvesting process, the design and development related to the dehanding machine, the cutting and crushing machine of bunch stalks, and the fiber extraction machine of bunch stalks are in the initial stages. In addi...
Mechanistic tumor growth models are widely used to describe disease progression and treatment response, but their utility depends on accurate estimation of parameters governing the underlying biological processes. In this study, we employ a Physics-I...
The main goal of this paper is to search for orbits that can be used in the Brazilian proposed Aster mission. This mission is under study and its objective is to use a spacecraft to observe the system 2001SN263, which is a triple asteroid system. Wit...
Concerning power systems, real-time monitoring of cyber–physical security, false data injection attacks on wide-area measurements are of major concern. However, the database of the network parameters is just as crucial to the state estimation process...
Accurate prediction of contact temperature in disconnectors is critical for early fault detection. However, purely physics-based models face difficulties in parameter identification, while purely data-driven models often suffer from error accumulatio...
This paper primarily presents statistics on the variation of physical characteristics (dimensions and mass) for the coulter discs of double-disc seeders. This statistic was calculated based on actual measurements of the probability density and cumula...
Several challenges hinder accurate and physically consistent dynamic parameter estimation in power systems, particularly under scenarios involving limited measurements, strong system nonlinearity, and high variability introduced by renewable integrat...
Physically consistent estimation of soft-tissue mechanical properties is critical for surgical robotics, intraoperative safety monitoring, and simulator initialization, yet existing methods typically require force-sensing hardware or manual parameter...
Modeling the dynamic response of saturated marine soils is crucial yet computationally challenging for traditional methods. Meanwhile, purely data-driven models suffer from sparse data and lack of physical interpretability. To overcome these limitati...
Background: Although the survival rates of childhood cancer are increasing, children diagnosed as having cancer experience psychological and physical problems and a declining quality of life (QOL). Methods: A systematic review of PubMed databases was...
Complex engineering systems—such as ultra-long horizontal wells in energy exploitation and distributed rail transit infrastructure—operate under harsh physical and environmental conditions, where accurate physical modeling and real-time p...
Tactile perception plays a crucial role in the perception of products and consumer preferences. This perception process is structured in hierarchical layers comprising a sensory layer (soft and smooth) and an affective layer (comfort and luxury). In...
Accurate digital twins (DTs) of multiphase permanent-magnet synchronous machines (PMSMs) remain challenging because nonlinear magnetic saturation, cross-coupling, iron-loss effects, and inverter non-idealities must be represented despite limited mach...
This paper presents the validation of a digital image analysis method for the quantitative determination of physical quality parameters of apples by comparative analysis with a traditional measurement method. The method was used to determine the qual...
In the current work, the exact analytical expression of the current–voltage characteristics, which are given in terms of the
In recent years, hybrid systems combining data-driven and physics-based approaches have gained increasing attention for solving complex real-world problems where deterministic modeling alone is insufficient. Within this framework, Physics-Informed Ne...
Field tests are the most suitable method to determine geotechnical parameters. Owing to some restrictions in field tests, physical modeling has been widely accepted as a proper method to define mathematical correlations among geotechnical parameters....
Promoting visual health in early childhood is crucial for visual development, and effective school-based interventions are urgently needed. This study examined the effects of physical exercise combined with accommodative training on visual acuity and...
This study developed a physics-informed neural network (PINN) surrogate model for a one-dimensional synthetic groundwater contaminant-transport problem with adsorption, using Crank–Nicolson numerical solutions as the reference data. The effects...
Background: Gender differences in metabolic response to lifestyle interventions remain poorly explored. This study aimed to evaluate the impact of a six-month Mediterranean diet (MD) intervention combined with regular physical activity on metabolic p...
9 June 2021
Age-related dementia refers to a state in which someone experiences multiple cognitive function impairment due to degenerative brain disease, and which causes difficulties in their daily life or social life. Dementia is the most common and serious ob...
Due to the presence of boulders and different morphologies, mountain rivers contain various resistance sources. To correctly simulate river flow using 1-D hydrodynamic models, an accurate estimation of the flow resistance is required. In this article...
We present a two-scale physics-informed neural network (TSPINN) algorithm to address structural parameter inversion problems involving small parameters. The algorithm’s core mechanism directly embeds small parameters into the neural network arc...
This study aimed to investigate the association of sarcopenia and type 2 diabetes (T2D) with blood parameters, nutrient intake, and physical activity in older Korean adults. We divided 2952 participants into four groups: sarcopenic diabetes (SD), sar...
Because of the growing consumer demand for healthy foods, new snacks have started to emerge as an alternative to the usual snacks regarded as nutritionally poor. The aim of this study was to develop functional maize snacks enriched with 5%, 10% and 2...
Oil-water two-phase flow commonly occurs in the process of crude oil electric dehydration. Here, through dynamic changes in the water content and conductivity of oil-water two-phase flow in the process of electric dehydration, the influence of water...
The nonlinear operational stiffness characteristics of machine tool spindles directly influence machining precision and bearing service life. Traditional static stiffness tests rely on direct differential operations on raw experimental load–dis...
Small-scale variation in the physical and biological properties of sea ice was examined by collecting nine sea ice cores within 1 m2 in a land-fast first-year ice in southwest Greenland in late winter. Cores were sectioned in four segments and sea ic...
Cabbage is a major leafy vegetable in China, but its post-harvest stubble—characterized by high lignification, a thick primary taproot, well-developed lateral roots, and strong root–soil anchorage—poses significant challenges for me...
The article presents a comparative analysis of published data for the physical parameters of the ZGP (ZnGeP2) crystal, its nonlinear and phase-matching properties, and functional capabilities for all frequency conversion processes (harmonics, sum and...
The main aim of this study is probabilistic computer simulation of the effective physical parameters of fluids containing nanoparticles. A deterministic model following the rule of mixtures and some semi-empirical formulas are employed to calculate e...
Accurate fault location is crucial for enabling maintenance personnel to quickly reach the fault site for inspection and repair, thereby minimizing power outage duration. To address the low fault location accuracy caused by phase unsynchronization of...
Accurate simulation of reinforced concrete (RC) members under cyclic loading requires hysteresis models that capture degradation and pinching, yet inverse identification of such models remains challenging because the internal-state evolution is stron...
Background/objective: Obesity and overweight have become growing health-related issues worldwide, which also applies to Poland. Excess fat mass is associated with an increased risk of metabolic and non-metabolic complications. The aim of our pre&ndas...
CO2 transport is a crucial part of CCUS. Nonetheless, due to the physical property differences between CO2 and natural gas and oil, CO2 pipeline transport is distinct from natural gas and oil transport. Gaseous CO2 transportation has become the prefe...
Quantitative estimates of reservoir parameters and elastic anisotropy using seismic methods is essential for characterizing shale oil reservoirs. Rock physics models were established to quantify elastic anisotropy associated with clay properties, lam...
The measurement of deep water gravity wave elevations using in situ devices, such as wave gauges, typically yields spatially sparse data due to the deployment of a limited number of costly devices. This sparsity complicates the reconstruction of the...
Reliable vibration prediction for gear systems requires calibration of uncertain mesh and bearing parameters. Previous gear physics-informed machine learning (PIML) studies mainly estimated time-varying meshing stiffness (TVMS) or calibrated gearbox...
Uncertain masses, dimensions, and friction coefficients can cause a robot’s motion to differ from predictions based on nominal parameters. This study examines how these uncertainties affect joint trajectories and which parameters deserve closer...
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