Physical Model Research Articles

Monte Carlo Workflow Unification for Nuclear Reactor Analysis with Metamodel-Driven Modeling

Monte Carlo (MC) transport codes are a cornerstone of nuclear reactor analysis frameworks, providing reference solutions and multigroup cross sections, and even as core components in multiphysics couplings. These applications can be seen in toolkits from the Nuclear Energy Advanced Modeling and Simulation program and the U.S. Nuclear Regulatory Commission’s BlueCRAB (Comprehensive Reactor Analysis Bundle). Contrary to their ubiquitousness in reactor physics modeling and simulation, popular MC codes, such as MCNP, Serpent, and KENO, are still reliant on antiquated textual input formats. These input languages use a plethora of keywords with terse syntax to specify all facets of a model, including its geometry, materials, physics settings, and tally options. This poses a steep learning curve and a poor user experience. Being tied to unique text-based input formats also significantly complicates programmatic input generation or modification that may be desired and/or required within a multiphysics framework. This work demonstrates how the development of programmatic interfaces for MC codes can support model unification and translation activities. Building on the Python application program interface (API) development of MCNPy, similar capabilities are being implemented for Serpent that are able to support model translation. In future work, the Serpent API capabilities will be made more robust and the work will be further expanded to include translations with KENO.

Methodology for the Interpretation of a Neural Network Model in Comparison to a Physical Model: A Fluid Catalytic Cracking Application

Methodology for the Interpretation of a Neural Network Model in Comparison to a Physical Model: A Fluid Catalytic Cracking Application

Impact of non-thermal phase-space distributions on dark matter abundance in secluded sectors

Many new physics models include secluded sectors that interact little with the Standard Model and whose internal interactions control the dark matter abundance. If these same interactions are responsible for maintaining kinematic equilibrium within the secluded sector, it is possible that the phase-space distributions will differ considerably from their thermal values during freeze-out. This can potentially result in deviations of the dark matter abundance from that computed under the assumption of thermal distributions. In this paper, we revisit dark matter abundance computations for a benchmark secluded sector by numerically tracking the phase-space distributions. Namely, we show that the dark matter abundance can deviate considerably from standard results during the freeze-out process, but that a longer period of annihilation ultimately leaves only a slight excess.

Peakons and compactons of the (2+1)-dimensional modified dispersive water-wave system

Abstract For a higher-dimensional nonlinear dynamical system, there exist abundant coherent excitations. The variable-separated method is a powerful approach to deriving these structures, as its solutions allow for arbitrary functions. Previous works have produced numerous results, including solitons, chaos and fractals. As the molecule structure appears, constructing the multi-soliton molecule through this technology is a meaningful work, especially considering the local peakons and compactons that were seldom discussed before. In this paper, after taking the Bäcklund transformation, the variable-separated solution for the (2+1)-dimensional modified dispersive water-wave system is first derived, which is an important physical model in describing the nonlinear and dispersive long gravity waves. As a result, the multi-peakons and multi-compactons are constructed through the derived universal formula with the aid of the variable functions p and q. These solitons include two general clusters of M×N peakons and compactons, from which the multi-soliton molecules and their interactions are presented.

Wind Tunnel Testing and Performance Modeling of an Atmospheric Ion Thruster

Abstract In this work a complete atmospheric EHD thruster is tested in a subsonic wind tunnel,
with the purpose of evaluating changes in performance due to simulated flight conditions
and, for the first time, comparing them with a physical model of the drift region. An
aerodynamic frame was designed to accommodate the electrodes inside the wind tunnel.
Propulsive force and electrical measurements were conducted to assess performance ex-
ploiting dimensionless coefficients derived from one-dimensional theory. The results, on
top of validating the theory, show how EHD thrusters can operate with a non-zero bulk
velocity and highlight the importance of optimized frames and electrodes to enhance the
capabilities of flying demonstrators. The test campaign revealed that the operating volt-
age envelope extends with increasing bulk velocity, leading to an increase in maximum
thrust.

Exploring the Opportunities and Barriers of Implementing the Health Focused Physical Therapy Model

The Health-Focused Physical Therapy Model integrates lifestyle behavior management into physical therapy practice using a standardized care model and motivational patient interviewing. The purpose of this study was to identify the perceived opportunities and barriers physical therapists, physical therapist assistants, and rehab administrators may face when implementing the model. This study included a survey of 19 physical therapy clinicians, and interviews with four rehabilitation administrators from one healthcare system. All participants attended a continuing education course covering the model and then completed a survey detailing their perceptions. Participants included female (100%), physical therapists (78.9%) and physical therapy assistants (21.1%), with variable educational degrees, and at least 16 years of clinic experience (73.7%). Four rehabilitation administrators, 100% female with at least 11 years of PT practice, participated in a semi-structured interview. Survey analysis revealed participants were confident in their understanding of the model and believed the model would positively impact the health of patients. However, over half perceived time limitations as a barrier. Meanwhile, three themes from the interview emerged including holistic care, implementation barriers, and needed resources. This study demonstrated time limitations and productivity standards could limit the implementation of health-focused physical therapy care. Future research should analyze opportunities and barriers of the model with broadened participant sampling methods and triangulation across healthcare practitioner roles to guide implementation and realistic practice standards.

Resonances crossing and electric field quantum sensors* *Andrea Sacchetti is member of Gruppo Nazionale per la Fisica Matematica of Istituto Nazionale di Alta Matematica (GNFM-INdAM). This work is partially supported by the Next Generation EU—Prin 2022CHELC7 project ‘Singular Interactions and Effective Models in Mathematical Physics’ and the UniMoRe-FIM project ‘Modelli e metodi della Fisica Matematica’.

We propose a theoretical model for a quantum sensor that can determine in a very simple way whether the intensity of an electric field has an assigned value or not. It is based on the fact that when an exact crossing of the imaginary parts of the resonances occurs in a double-well quantum system subject to an external DC electric field, a damped beating phenomenon occurs, which is absent if there is no such a crossing. This result is then tested numerically on an explicit one-dimensional model.

How many new particles do we need?

The Standard Model of particle physics (SM) and Einstein general relativity are extremely successful in describing almost all phenomena observed in Nature so far, spanning distances from a fraction of Fermi to thousands of megaparsec (Mpc). In this review article, the author deliberates on the question formulated in the title, given that the SM does not allow neutrino oscillations, does not have a candidate for dark matter in the Universe, and does not explain the observed cosmological dominance of matter over antimatter.

Aero-optical effects of a hypersonic vehicle based on the refractive index step ray tracing method

The aero-optical effect caused by the high-speed flight of aircraft can affect the accuracy of astronomical navigation, so studying the laser transmission characteristics in high-speed flow fields is essential. This study adopts a 3D spherical blunt cone model as the physical aircraft model, incorporates the latest reanalysis data from the National Centers for Environmental Prediction as atmospheric parameters, and uses Fluent software to establish a hypersonic aircraft external flow field model. The ray tracing error is calculated using a method based on the refractive index step size. Results indicate that, under the conditions of flying altitude of 5 km and incident angle of 45°, the proposed ray tracing method has better accuracy than the traditional method. Compared with the Runge–Kutta method and the method based on geometric step size, the proposed ray tracing method reduces the error by 46.4% and 12.5%, respectively, at the flight Mach number of 5.

Multi-Body Model of Agricultural Tractor for Vibration Transmission Investigation

This article analyses vibration transmission on agricultural tractors with the excitation from the road to the driver’s seat. A multi-body model of agricultural tractors created in Adams is presented. The main parts for the investigation of vibration transmission are the tractor body, where the only suspension elements are tyres, the tractor cabin, spring-dampers suspended at the rear and bushings at the front, and the driver seat with its pneumatic spring. A series of measurements were performed, and the model was validated using vertical acceleration values on the tractor body at four different locations. The FTire model (physical FEM-based model) was chosen to describe the behaviour of tyres. The model was created using measured tyre characteristics. Measured characteristics of spring-dampers and front cabin bushings were also implemented. For comfort investigation, ride simulations on ISO 5008 rough roads were performed. The transmission of vibrations in ride simulations was examined. A modal analysis of the linearised model was performed to confirm assumptions of the contribution of suspension elements to overall vibration levels. Finally, three case studies were conducted to better understand the model’s vibration transmission properties.

Bonner sphere measurements of high-energy neutron spectra from a 1 GeV/u 56Fe ion beam on an aluminum target and comparison to spectra obtained by Monte Carlo simulations

The goal of this work is to characterize the secondary neutron spectra produced by 1 GeV/u56Fe beam colliding with a thick cylindric aluminum target and to perform a quantitative comparison with simulated results obtained with Monte Carlo codes. The measurements were performed using extended-range Bonner sphere spectrometers at two positions (15° and 40°) with respect to the beam direction. The secondary radiation field was simulated using four Monte Carlo codes (FLUKA, MCNP6, Geant4 and PHITS) and several physical models of nuclei transport and interaction. Neutron and proton energy distributions were simulated for the experimental measurement positions. The simulated neutron spectra, together with data measured with Bonner sphere spectrometers, after carrying out the correction of the contributions induced by the secondary protons, were used as input for the MAXED spectrum unfolding code to obtain the measured neutron spectra. Unfolded neutron spectra were compared with simulated ones to carry out a quantitative analysis of the performance of the chosen Monte Carlo codes and their corresponding physical models. This comparison showed that, because of experimental uncertainties and physical models, there are no unique solutions for each measurement location, but a range of solutions where the true experimental neutron spectra probably lie. The results showed deviations between 4.23% and 8.42% for some simulated spectra. Regarding the total integral values of neutron fluence and ambient equivalent dose, the unfolded neutron spectra showed deviations lower than 2%.

Performance of a Cable-Driven Robot Used for Cyber–Physical Testing of Floating Wind Turbines

Cyber–physical testing has been applied for a decade in hydrodynamic laboratories to assess the dynamic performance of floating wind turbines (FWTs) in realistic wind and wave conditions. Aerodynamic loads, computed by a numerical simulator fed with model test measurements, are applied in real time on the physical model using actuators. The present paper proposes a set of short and targeted benchmark tests that aim to quantify the performance of actuators used in cyber–physical FWT testing. They aim at ensuring good load tracking over all frequencies of interest and satisfactory disturbance rejection for large motions to provide a realistic test setup. These benchmark tests are exemplified on two radically different 15 MW FWT models tested at SINTEF Ocean using a cable-driven robot.

Transient NOx emission modeling of a hydrogen-diesel engine using hybrid machine learning methods

One promising approach to reduce carbon foot print of internal combustion engines (ICEs) is using alternative fuels like hydrogen, particularly by converting medium and heavy-duty diesel engines to dual-fuel hydrogen-diesel engines. To minimize elevated NOx emissions from hydrogen-fueled engine, fast and accurate emission models are essential for engine model-based control and for engine calibration and optimization using hardware-in-the-loop (HIL) setups. In this study, a fast-response NOx emissions sensor is used to measure the transient NOx emissions from a dual-fuel hydrogen-diesel engine. Subsequently, steady-state models (SSMs), quasi steady-state models (QSSMs), and transient sequential models (TSMs) in the form of black-box (BB) and gray-box (GB) models are developed for transient NOx emissions prediction. GB models utilize both information from a one dimensional (1D) physical engine model and experimental data for training, while BB models only use experimental data. SSMs are optimized artificial neural networks (ANNs) trained using steady-state data, QSSMs are optimized ANNs trained using transient data, and TSMs are time-series networks trained using transient data. Long short-term memory (LSTM) and gated recurrent unit (GRU) networks are used as the time-series deep learning networks. The results showed that the 1D physical model has the poorest performance with successive model performance improvement from SSM to QSSM and from QSSM to TSM. The developed BB TSM model in this study can predict transient NOx emissions with an R2 value greater than 0.96 at 89,000 predictions per second which makes this model suitable for real-time engine model-based control where computational efficiency is crucial. The developed GB TSM model can predict transient NOx emissions with an R2 value greater than 0.97 but it is computationally more expensive. The extra accuracy of the GB TSM models makes them the best choice for HIL setups where more computational power is available, and accuracy is more crucial.

Why We Eat Calories: A Plurality Metaphor of Energy in Scientific Disciplines

AbstractIn the Next Generation Science Standards, energy is considered a “crosscutting concept” that bridges disciplinary boundaries and unites scientific disciplines. I examine how energy is represented in physics, biology, and chemistry contexts, using the reaction of molecular oxygen with sugar as an exemplar, and argue that disciplines disagree in how they represent the origin of energy that drives this process. In particular, while biology tends to locate energy as initially in the sugar molecule, chemistry locates the energy in molecular oxygen, and physics models energy as in the field between the molecules. That is to say, biology describes us as eating calories, chemistry as inhaling calories, and physics invents an abstract object (the field) as the container for energy. I then show how the conceptualizations made in each discipline stem from core disciplinary commitments, models, and concepts that structure what “counts” as an explanation. This conceptual plurality, then, is essential to disciplinary meaning. While such a pluralistic conceptualization appears to be contrary to scientific epistemology that prioritizes coherence and cognitive models that rely on unitary structures for transfer, I draw on recent research to argue that neither concern is fully founded. Finally, I suggest that building bridges between these contrasting conceptualizations may come later, in response to interdisciplinary questions and frameworks.

Development and assessment of case-specific physical and augmented reality simulators for intracranial aneurysm clipping

BackgroundMicrosurgical clipping is a delicate neurosurgical procedure used to treat complex Unruptured Intracranial Aneurysms (UIAs) whose outcome is dependent on surgeon’s experience. Simulations are emerging as excellent complements to standard training, but their adoption is limited by the realism they provide. The aim of this study was to develop and validate a microsurgical clipping simulator platform.MethodsPhysical and holographic simulators of UIA clipping have been developed. The physical phantom consisted of a 3D printed hard skull and five (n = 5) rapidly interchangeable, perfused and fluorescence compatible 3D printed aneurysm silicone phantoms. The holographic clipping simulation included a real-time finite-element-model of the aneurysm sac, allowing interaction with a virtual clip and its occlusion. Validity, usability, usefulness and applications of the simulators have been assessed through clinical scores for aneurysm occlusion and a questionnaire study involving 14 neurosurgical residents (R) and specialists (S) for both the physical (p) and holographic (h) simulators by scores going from 1 (very poor) to 5 (excellent).ResultsThe physical simulator allowed to replicate successfully and accurately the patient-specific anatomy. UIA phantoms were manufactured with an average dimensional deviation from design of 0.096 mm and a dome thickness of 0.41 ± 0.11 mm. The holographic simulation executed at 25–50 fps allowing to gain unique insights on the anatomy and testing of the application of several clips without manufacturing costs. Aneurysm closure in the physical model evaluated by fluorescence simulation and post-operative CT revealed Raymond 1 (full) occlusion respectively in 68.89% and 73.33% of the cases. For both the simulators content validity, construct validity, usability and usefulness have been observed, with the highest scores observed in clip selection usefulness Rp=4.78, Sp=5.00 and Rh=4.00, Sh=5.00 for the printed and holographic simulators.ConclusionsBoth the physical and the holographic simulators were validated and resulted usable and useful in selecting valid clips and discarding unsuitable ones. Thus, they represent ideal platforms for realistic patient-specific simulation-based training of neurosurgical residents and hold the potential for further applications in preoperative planning.

Discovery of SRGA J144459.2-604207 with the SRG/RT-XC telescope : A well-tempered bursting accreting millisecond X-ray pulsar

We report the discovery of the new accreting millisecond X-ray pulsar SRGA\,J144459.2$-$604207 using data of the SRG The source was observed twice in February 2024 during the declining phase of the outburst. The timing analysis revealed a coherent signal near 447.9 Hz modulated by the Doppler effect due to the orbital motion. The derived parameters for the binary system are consistent with a circular orbit with a period of sim 5.2 h. The pulse profiles of the persistent emission, showing a sine-like part during half a period with a plateau in between, can be well modeled by emission from two circular spots that are partially eclipsed by the accretion disk. Additionally, during our observations with an exposure of 133 ks, we detected 19 thermonuclear X-ray bursts. All bursts have similar shapes and energetics, and none show any signs of an expanding photospheric radius. The burst recurrence times decreases linearly from sim 1.6 h at the beginning of observations to sim 2.2 h at the end and anticorrelate with the persistent flux. The spectral evolution during the bursts is consistent with the models of the neutron star atmospheres that are heated by accretion and implies a neutron star radius of 11--12 km and a distance to the source of 8--9 kpc. We also detected coherent pulsations during the bursts and showed that the pulse profiles differ substantially from those observed in the persistent emission. However, we could not find a simple physical model explaining the pulse profiles detected during the bursts.

Квантовые вычисления в медицинской физике: особенности алгоритмов и их перспективы

Background: Quantum computing represents a paradigm leap in computational capabilities, with potential applications across various scientific disciplines. The complicated computations required for imaging, radiation therapy, and molecular modeling in medical physics give novel prospects for quantum computing. Objective: This article investigates the role of quantum computing in medical physics research, with an emphasis on its potential to improve computational efficiency and accuracy and develop novel treatment approaches. Methods: A thorough literature analysis was undertaken to investigate recent advances in quantum computing and their implications in medical physics. Case studies were reviewed to demonstrate practical applications and possible advantages. Theoretical models were tested to forecast future developments. Statistical data from quantum computing implementations were gathered from many sources, particularly on improving processing speed and accuracy in medical physics applications. Results: The findings show that quantum computing can significantly improve the processing speed of complex simulations and imaging techniques, with some quantum algorithms outperforming classical algorithms by up to 100 times. In radiation therapy planning, quantum computing has exhibited a 25% boost in dose distribution calculation precision. Quantum algorithms have lowered calculation times in molecular modeling by about 40%, potentially boosting drug development and customized therapy by 30%. Conclusion: Quantum computing has the potential to alter medical physics by increasing computational capacity, which could lead to advancements in diagnostics, treatment planning, and medication development. The statistical results corroborate the promise of quantum computing in these domains, emphasizing the importance of ongoing interdisciplinary collaboration and research to fully achieve these benefits and address present hurdles in incorporating quantum computing into clinical practice.

Prediction of the minimum miscibility pressure for CO2 flooding based on a physical information neural network algorithm

Abstract The minimum miscibility pressure (MMP) is a crucial parameter in assessing the miscibility of CO2 displacement and evaluating the effectiveness of oil displacement. Traditional methods for calculating MMP are intricate and time-consuming, involving numerous related parameters. Therefore, precise and efficient determination of MMP is highly significant in the development of CO2-driven reservoirs. This study first utilized the Pearson correlation coefficient to analyse the correlation factor mechanism of 36 sets of fine-tube experimental data. Subsequently, the physical information neural network prediction model was employed with reservoir temperature, crude oil composition, and injected gas type as input parameters. The PRI state equation and Glaso correlation equation drove the model, with parameter optimization and training conducted under both physical and data driving. The model demonstrates high prediction accuracy and strong generalization ability. Finally, Validation of the model was performed using fine-tube experimental data from 5 other wells, revealing a relatively small relative deviation between calculated and experimental values, with an average coefficient of determination of 0.95 and an average relative error of 4.42%. The prediction accuracy was improved by about 75% compared to other machine learning algorithms. This model holds potential for application in on-site reservoir development, enhancing the measurement accuracy of the minimum miscible pressure of pure CO2 flooding, greatly shortening the design cycle of reservoir development, expediting the process of reservoir development, and providing technical guidance for improving oil and gas recovery and pure CO2 flooding exploration and development.

Influence of Central Coke Ratio on the Internal State of Blast Furnace

Central coke charging (CCC) is a widely used burden distribution method for blast furnaces (BFs). Adjusting the central coke ratio can change the burden temperature field and affect the smooth operation of BF. This study presents a coupled physical and mathematical model, incorporating particle motion, gas flow, and heat transfer between the burden and gas in two 5500 m3 BFs. The central coke ratios of the blast furnace A (BFA) and blast furnace B (BFB) is 15% and 20%, respectively. The root positions of the cohesive zone in the BFA and BFB are in the lower part of the stack and bosh zones, respectively. In the central area of the BF, the gas flow rate, gas temperature, and burden temperature of the BFB are higher. In the edge area of the BF, the gas flow rate, gas temperature, and burden temperature of the BFA are higher. The actual top gas temperature and gas pressure verify the accuracy of the proposed model. This model investigates the influence of the central coke ratio on the position of the cohesive zone, gas flow rate, gas temperature, and burden temperature, providing a cost‐effective method for studying the effect of the burden distribution matrix on the internal state of the BF.

A Novel Impedance-Based Parallel Cooperative Control Method for Front and Rear Landing Gear Hydraulic Systems of UAVs

Cargo handling issues affect the ability of large heavy-duty Unmanned Aerial Vehicles (UAVs) to transport cargo and limit the development of large UAVs. Compared to conventional landing gear, hydraulically controlled landing gear can tilt the drone within a specified angle, facilitating smoother loading and unloading of goods. Therefore, it is important to study the hydraulic landing gear control system for a UAV to make the UAV’s tilt possible. In this paper, an impedance-based parallel cooperative control method for front and rear landing gear hydraulic systems of large heavy-duty UAVs is presented, which can achieve UAV tilting within a reasonable angle during the loading and unloading of cargoes by large, heavy-duty UAVs. This paper establishes the physical model of the UAV’s landing gear, the mathematical model of the hydraulic system, and the kinematic model of the airframe. Through kinematic analysis, the correlation between each hydraulic dive unit’s (HDU’s) extension length in the landing gear and the UAV’s tilt angle is established. This paper introduces a two-fold based-loop parallel control technique, featuring angle based-loop control for the UAV’s front and position based-loop control for its rear landing gear. It aims to enable the UAV to freely tilt for loading and unloading cargo at a predetermined angle, by measuring the UAV’s tilting angle, the HDU’s force exerted on the landing gear, and its positional parameters. Ultimately, the practicality of this technique is confirmed through simulations and experiments.