Accurate Simulation Research Articles

Research on modeling method for connectors in the train-track-bridge system based on multi-timestep explicit-implicit co-simulation

For the response of the train-track-bridge system under extreme environment, an increasing number of studies employ co-simulation strategies for detailed modeling and calculation of the structure. However, there is a lack of research on the module connectors, which significantly impact simulation accuracy and stability. In this paper, the theoretical differences between weak, moderate, and strong coupling methods in dealing with co-simulation module interface connectors are discussed. An explicit-implicit multi-timestep co-simulation platform is established using MATLAB and OPENSEES software. Taking China's CRTS II slab ballastless track, a simply supported beam bridge, and a train as examples, a three-dimensional train-track-bridge coupling model is created. The three coupling methods are then verified and compared. Finally, two coupling methods are used to model and calculate the train-track-bridge system under earthquake. It is concluded that when calculating the train-track-bridge under earthquake, using the fastener with less damage as the co-simulation partition boundary can avoid complex nonlinear calculation. On this basis, it is feasible to use weak, moderate and strong coupling methods to deal with fastener elements. Different co-simulation software can adopt different coupling methods according to the difficulty of modeling. In the MATLAB-OPENSEES multi-timestep explicit-implicit co-simulation platform, the weak and moderate methods can achieve better calculation accuracy, and can be used to calculate the response of train-track-bridge system under earthquake.

Research on the simulation method of a BP neural network PID control for stellar spectrum

This study investigated the multiple correlations among spectral simulation units based on digital micromirror device (DMD) spectral simulation, which leads to the problem that conventional spectral simulation methods such as PID control exhibit a low fitting accuracy or long fitting time in the spectral simulation of various targets. In this paper, a method of stellar spectrum simulation based on back propagation neural network-based PID (BP-PID) control is proposed to achieve high efficiency and high precision simulation of various spectral targets. The topology of the BP neural network was constructed based on the spectral modulation model of a DMD stellar spectrum simulation system, and the algorithm of the BP-PID control was designed. Finally, an experimental platform was built to verify the performance and spectral simulation accuracy of the BP-PID control algorithm. The results show that the overshoot and response time of the BP-PID control algorithm decreased by 79.01% and 30%, respectively compared with those of the PID control algorithm. The maximum spectral simulation accuracies of 2000K, 7000K, and 12000K color temperature increased by a factor of 2.311, 1.871, and 2.254, respectively, and the standard deviations of the spectral simulation error decreased by 56%, 41%, and 54%, respectively. In the range of 2000-12000K color temperature, the spectral simulation error of the BP-PID control algorithm is better than ±3.495%, and the standard deviation of the spectral simulation error is between 1.8255 and 2.2358. The proposed method can improve the spectral simulation accuracy and simulation efficiency of a star simulator, reduce the magnitude and spectrum calibration errors caused by the differential response, improve the star feature recognition accuracy of the orbiting star sensor, and hence, provide a theoretical and technical basis for the development of high-precision star sensors.

A simplified method for theoretical sum frequency generation spectroscopy calculation and interpretation: The "pop model".

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 abinitio 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.

How does PM2.5 affect forest phenology? Integrating PM2.5 into phenology models for warm-temperate forests in China

Vegetation can regulate particulate matter (PM) through various mechanisms, such as facilitating the deposition of gases and particulates and purifying the air via photosynthesis. Conversely, PM directly damages leaves through dry deposition, while it also indirectly affects plant growth by altering weather conditions. However, the ways in which PM influence vegetation growth patterns, and the driving factors behind these impacts, remain unclear. In this study, we primarily focused on the start of the growing season (SOS) of warm-temperate zone forests in China with severe PM. SOS exhibited a trend of advancing at a rate of 0.15 days/yr during the study period from 2004 to 2022. We assessed the impact of satellite-derived fine PM (PM2.5) and coarser PM (PM10) on forest SOS across warm temperate forest regions in China using partial correlation analysis methods. After removing the effects of PM, we found that the correlation between temperature and SOS weakened. Additionally, PM exhibited a positive correlation with SOS in most pixels. Linear regression analysis revealed a significant negative correlation between relative humidity (RH) and the relationship between PM2.5 and SOS. However, in areas where RH exceeds 60.38%, this effect becomes unstable, presumably due to increased aerosol hygroscopicity or the saturation of aerosol particles. We also found that as road network density increased, the relationship between PM2.5 and SOS strengthened, whereas the impact of nightlight on this relationship was relatively weak. It is important to note that while the observed correlations reveal mechanisms by which PM2.5 affects SOS, they do not directly imply causation, as the complex interactions between environmental factors may influence these relationships. Finally, we incorporated PM2.5 into the phenology model and optimized its parameters using the least squares method, which improved the accuracy of SOS simulations and provided insights for predicting vegetation phenology in areas with severe PM pollution.

Quantum computing with error mitigation for data-driven computational homogenization

As a crossover frontier of physics and mechanics, quantum computing is showing its great potential in computational mechanics. However, quantum hardware noise remains a critical barrier to achieving accurate simulation results due to the limitation of the current hardware. In this paper, we integrate error-mitigated quantum computing in data-driven computational homogenization, where the zero-noise extrapolation (ZNE) technique is employed to improve the reliability of quantum computing. Specifically, ZNE is utilized to mitigate the quantum hardware noise in two quantum algorithms for distance calculation, namely a Swap-based algorithm and an H-based algorithm, thereby improving the overall accuracy of data-driven computational homogenization. Multiscale simulations of a 2D composite L-shaped beam and a 3D composite cylindrical shell are conducted with the quantum computer simulator Qiskit, and the results validate the effectiveness of the proposed method. We believe this work presents a promising step towards using quantum computing in computational mechanics.

A Non‐Iterative Wheel‐Rail Contact Geometry Determination Algorithm and Its Application

AbstractTo ensure a more accurate simulation of the wheel‐rail contact state in vehicle‐track interaction, a non‐iterative contact geometry determination algorithm is proposed. This algorithm decouples lateral movement and roll, independently calculates the minimum wheel‐rail gap on both sides, and overcomes the limitation of simultaneous wheel‐rail contact on both sides. It can be applied to single‐side and two‐side wheel‐rail separation problems. Additionally, by converting track irregularity and rail deformation into the reverse displacement of the wheel, it avoids real‐time calculation of the wheel‐rail spatial position, thereby improving calculation efficiency. The effectiveness of the algorithm is verified through Universal Mechanism software and field measurements. Subsequently, the influence of the measured wheel‐rail profile, rail cant, and rail gauge on the wheel‐rail contact characteristics is analyzed. Finally, vehicle shaking caused by track irregularity and wheel‐rail contact is examined from the perspective of wheel‐rail matching. The study demonstrates that the non‐iterative algorithm is suitable for online simulation by pre‐processing the contact geometry parameters. When the track gauge and rail cant increase, the distribution of wheel‐rail contact points becomes more concentrated. Furthermore, when the excitation frequency of wheel‐rail matching is close to the track irregularity excitation frequency, it causes vibration amplification, resulting in lateral vehicle shaking.

Unified non-hourglass formulation for total Lagrangian SPH solid dynamics

AbstractThe persistence of hourglass modes poses a significant numerical instability issue in total Lagrangian smoothed particle hydrodynamics (TLSPH) solid dynamics, especially when dealing with substantial deformations, regardless of material properties. However, existing hourglass control methods have shown effectiveness only within limited applications. Thus far, a comprehensive solution capable of addressing hourglass issues across a wide range of material models, including elasticity, plasticity, and anisotropy, remains elusive. In this study, we introduce a unified TLSPH formulation grounded in volumetric-deviatoric stress decomposition, aimed at fundamentally mitigating hourglass modes in general simulations. Different conceptually from previous approaches using stress points or extra viscous or hourglass-control stresses within the momentum equation, our formulation is based on the weighted average of a standard but hourglass-prone formulation and an essentially non-hourglass formulation for elastic materials, employing a single limiter to dynamically adjust the weighting between the two formulations. Crucially, the dimensionless characteristic of the formulation enables seamless handling of complex material models. To validate the effectiveness of our formulation, we conduct simulations across a range of benchmark cases involving elastic, plastic, and anisotropic materials. To illustrate its versatility, we apply the formulation to simulate a complex scenario involving viscous plastic Oobleck material, contacts, and very large deformation. Our work addresses a critical gap in TLSPH simulations by offering a unified approach to mitigate hourglass modes, enhancing the reliability and accuracy of simulations across diverse material models and complex scenarios.

Optimizing modern surgical simulation through instructor feedback - insights from a retrospective observational study in a tertiary hospital.

Laparoscopic surgery is associated with a prolonged learning curve for emerging surgeons, and simulation-based training (SBT) has become increasingly prominent in this context due to stringent working time regulations and heightened concerns regarding patient safety. While SBT offers a safe and ethical learning environment, the accuracy of simulators in the context of evaluating surgical skills remains uncertain. This study aims to assess the precision of a laparoscopic simulator with regard to evaluating surgical performance and to identify the instructor's role in SBT. This retrospective study focused on surgical residents in their 1st through 5th years at the Department of Surgery of Linkou Chang Gung Memorial Hospital. The residents participated in a specially designed SBT program using the LapSim laparoscopic simulator. Following the training session, each resident was required to perform a laparoscopic procedure and received individualized feedback from an instructor. Both simulator and instructor evaluated trainees' performance on the LapSim, focusing on identifying correlations between the simulator's metrics and traditional assessments. Senior residents (n = 15), who employed more complex laparoscopic procedures, exhibited more significant improvements after receiving instructor feedback than did junior residents (n = 17). Notably, a stronger correlation between the simulator and instructor assessments was observed in the junior group (junior Global Operative Assessment of Laparoscopic Skills (GOALS) adjusted R2 = 0.285, p = 0.016), while no such correlations were observed among the senior group. A well-designed, step-by-step SBT can be a valuable tool in laparoscopic surgical training. LapSim simulator has demonstrated its potential in assessing surgical performances during the early stages of surgical training. However, instructors must provide intuitive feedback to ensure appropriate learning in later stages.

Shooting Simulator «Inhibitor»: Mathematical Support of Shot Special Effects

The algorithms for preparing shooters to perform an exercise, conducting its course with real-time informing, as well as the implementation of mathematical support of shot special effects (sounds, tracers, explosions, hits, and misses) for the optical-electronic shooting simulator 'Inhibitor' developed at Institute of Mechanics UdmFRC UB RAS and at facilities of Computer Department of Kalashnikov ISTU jointly with JSC «Kalashnikov» Concern» are described. A tactical and technical task is given for the visual and sound effects of a shot, such as tracers, grenade ruptures, misses, return fire, and controlled flight of PTURS. In addition, the manager must monitor the weapon simulator sensors during the preparation of the exercise (magazine, fire switch, cartridge inside the barrel and sight readings) and conduct the course of the exercise with real-time viewing of both targets and shots and altering the ammunition number and type (all ammunition can be made tracer ones). The arrows are selected from the department database for convenience. Viewing shooting errors and aiming along with hit points allows correction of trainees’ actions by means of commands and quick display service information for trainee independent classes on the projection screen. The study the factors affecting ballistic dispersion was carried out and the recommendations for its modeling were formulated. The literature review confirms the potential of further research and development of electronic rifle simulators via improvement of computational tools and the development of software libraries in order to increase the accuracy of shot process simulation and flexible display adjustment of current training exercise results. It is necessary to expand realistic opportunities of shot special effects and reduce the cost constantly, which means to increase the competitiveness of electronic shooting simulators.

A Composite Approach for Evaluating Operational Cloud Seeding Effect in Stratus Clouds

Robust water management is in intense demand in many water scarcity areas, such as arid and semi-arid regions in the world. As part of the regional water management strategy, rain enhancement is vital to replenish groundwater reservoirs, and the key challenge is how to assess its effectiveness. Some recent weather modification experiments attained cloud seeding effect through advanced in situ measurement coupled with accurate numerical simulation. However, there is still a lack of an objective and scientific approach to quantitatively evaluate the rain enhancement effect, especially for many non-randomized operational cloud seeding activities in China. In this study, we proposed a composite evaluation approach by analyzing two operational aircraft cloud seeding cases in stratus clouds in Shaanxi, China. By calculating the aircraft cloud seeding agent plumes, the target areas (as well as the control areas) of cloud seeding were dynamically and roughly determined. Physical properties, such as radar reflectivity and precipitation, were individually quantified in these areas. The cloud seeding effect was then evaluated by calculating the difference in parameter variation between target and control areas. This approach can be applied to qualitative analysis in a single aircraft cloud seeding operation and can also provide quantitative statistical results from multiple cloud seeding cases. We found that the average precipitation enhancement percentage of 18 operational aircraft cloud seeding cases is ~4.84%. Note that the homogeneity hypothesis of the seeding cloud, the error in the calculation of the target area, and the selection of control areas are the major uncertainties likely in the evaluation of the cloud seeding effect by this approach.

Comparative Assessment of Water Models in Protein-Glycan Interaction: Insights from Alchemical Free Energy Calculations and Molecular Dynamics Simulations.

Accurate computational simulations of protein-glycan dynamics are crucial for a comprehensive understanding of critical biological mechanisms, including host-pathogen interactions, immune system defenses, and intercellular communication. The accuracy of these simulations, including molecular dynamics (MD) simulation and alchemical free energy calculations, critically relies on the appropriate parameters, including the water model, because of the extensive hydrogen bonding with glycan hydroxyl groups. However, a systematic evaluation of water models' accuracy in simulating protein-glycan interaction at the molecular level is still lacking. In this study, we used full atomistic MD simulations and alchemical absolute binding free energy (ABFE) calculations to investigate the performance of five distinct water models in six protein-glycan complex systems. We evaluated water models' impact on structural dynamics and binding affinity through over 5.8 μs of simulation time per system. Our results reveal that most protein-glycan complexes are stable in the overall structural dynamics regardless of the water model used, while some show obvious fluctuations with specific water models. More importantly, we discover that the stability of the binding motif's conformation is dependent on the water model chosen when its residues form weak hydrogen bonds with the glycan. The water model also influences the conformational stability of the glycan in its bound state according to density functional theory (DFT) calculations. Using alchemical ABFE calculations, we find that the OPC water model exhibits exceptional consistency with experimental binding affinity data, whereas commonly used models such as TIP3P are less accurate. The findings demonstrate how different water models affect protein-glycan interactions and the accuracy of binding affinity calculations, which is crucial in developing therapeutic strategies targeting these interactions.

Daily NO2 Simulation Research Based on Automatic Machine Learning Ensemble Models

To understand the spatial distribution of NO2 near the surface, we utilized measured data from NO2 monitoring stations and combined it with column concentration data from the Tropospheric Monitoring Instrument （TROPOMI）, taking the Yangtze River Delta region as the study area. We considered the impact of factors such as population, elevation, and meteorological conditions on NO2 levels. We used automated machine learning to select five machine-learning algorithms with high simulation accuracy, namely ET, RF, XGBoost, LightGBM, and Catboost, and then integrated these five algorithms using the Stacking model to simulate the daily NO2 concentration in the Yangtze River Delta region from March 2020 to February 2021. The results indicated that the RMAE and MAE values of the Stacking ensemble model were 7.078 and 5.270, respectively, which outperformed the single algorithms of ET, RF, XGBoost, LightGBM, and Catboost. The spatial distribution of high NO2 concentrations in the Yangtze River Delta region, consisting of three provinces and one municipality, exhibited a U-shaped pattern with the convergence point located at the intersection of the three provinces, extending towards the southwest. Notably, urban pollution was particularly significant in the urban agglomerations centered around Shanghai, Hangzhou, Nanjing, and Hefei. There were 27 cities that exceeded the national standard daily limit. Changzhou was the city with the most serious NO2 pollution, with the NO2 concentration exceeding the standard for 14 d, followed by Shanghai, with 13 d. In terms of seasonal variation, the order of severity was as follows： winter, autumn, spring, and summer, with the least NO2 pollution occurring on July 9th during the summer, and the most severe NO2 pollution was observed on December 23rd during the winter.

Artificial intelligence‐driven sustainability: Enhancing carbon capture for sustainable development goals– A review

AbstractArtificial intelligence (AI) and environmental points are equally important components within the response to local weather change. Therefore, based on the efforts of reducing carbon emissions more efficiently and effectively, this study tries to focus on AI integration with carbon capture technology. The urgency of tackling climate change means we need more advanced carbon capture, and this is an area where AI can make a huge impact in how these technologies are operated and managed. It will minimize manufacturing emissions and improve both resource efficiency as well as our planet's environmental footprint by turning waste into something of value again. Artificial intelligence could be leveraged to analyze huge data sets from carbon capture plants, searching for optimal system settings and more efficient ways of identifying patterns in the available information at a larger scale than currently possible. In addition, AI incorporated sensors and monitoring mechanisms in the supply chain can identify any operational failure at reception itself allowing for timely action to protect those areas. Artificial intelligence also helps generative design for carbon capture materials, which allows researchers to explore new types of carbon‐absorbing material, including metal–organic frameworks and polymeric materials that are important in industrial CO2, such as moisture. In addition, it increases the accuracy of reservoir simulations and controls CO2 injection systems for storage or enhanced oil recovery. Through applying AI algorithms on reservoir geology, production performance and real‐time data this study would like to facilitate the optimization of injection processes as well as minimize CO2 emissions while assuring a maximum efficiency. Artificial intelligence integrates with renewable‐based carbon capture efforts that can be employed by AI‐driven smart grid systems to improve carbon capture methods.

Development of an improved mass transfer model for condensation with dynamic feedback regulation

In the field of condensation research, accurate and efficient numerical simulation models are highly desired. One of the widely used phase change mass transfer models is known as the Lee model. However, this model has limitations due to uncertainties in the mass transfer intensity factor, which can lead to simulation failures and impede large-scale engineering applications. This study presents an improved mass transfer model which employs a tuning function to dynamically and accurately modify the mass transfer intensity factor in each two-phase cell via feedback adjustment. This approach enables immediate and customized adjustment of the factor for each grid within the limit of the tuning function, significantly reducing the errors caused by repeated artificial adjustments and related uncertainties. The adjustment capabilities of the hyperbolic tangent and softsign functions are evaluated. The softsign function is superior in both regulation efficiency and accuracy. The model's accuracy is verified by comparing with previous experiments and simulations, as well as by the one-dimensional Stefan problem. The proposed model achieves high prediction accuracy, reduces the risk of simulation dispersion, and significantly enhances computational efficiency with the iteration number reduced by nearly half under certain conditions compared to the Lee model. Furthermore, the new model shows robustness as the prediction accuracy is insensitive to variations in critical parameters. The improved model is expected to provide valuable assistance for future research and applications in flow condensation with outstanding computational accuracy, efficiency, and stability.

Modeling sediment movement in the shallow-water framework: A morpho-hydrodynamic approach with numerical simulations and experimental validation

This work presents a morpho-hydrodynamic model and a numerical approximation designed for the fast and accurate simulation of sediment movement associated with extreme events, such as tsunamis. The model integrates the well-established hydrostatic shallow-water equations with a transport equation for the moving bathymetry that relies on a bedload transport function. Subsequently, this model is discretized using the path-conservative finite volume framework to yield a numerical scheme that is not only fast but also second-order accurate and well-balanced for the lake-at-rest solution. The numerical discretization separates the hydrodynamic and morphodynamic components of the model but leverages the eigenstructure information to evolve the morphologic part in an upwind fashion, preventing spurious oscillations. The study includes various numerical experiments, incorporating comparisons with laboratory experimental data and field surveys.

Advancements in railway noise simulation: assessment of tools for virtual validation

In pursuit of more efficient and cost-effective measurement campaigns, the railway industry is embracing the prospect of virtual validation based on simulations. The primary obstacle lies in the need for noise simulation tools capable of accurately replicating complex sources, installation effects, noise propagation, ground reflection and, for some cases, the diffraction in the different train surfaces. This paper presents insights derived from European project Shift2Rail S2R-CFM-CCA-01-2019 Energy and Noise & Vibration WP6, concentrating on the validation and enhancement of two exterior noise simulation tools, tailored for railway applications. The paper covers four reference cases, simulating exterior noise at standstill with diverse noise sources and varying source locations and noise emission (i.e. electrical noise, cooling, etc.). A correlation with previously conducted measurements at typical receiver locations (7.5 meters from the track centerline) is carried out. The measurements were conducted in a "controlled" configuration, isolating as much as possible the analyzed noise source and gathering all the needed information about the ground and train geometry. The evaluation between measurements and simulations is done against a global and a 1/3rd octave band criteria with successful results. Finally, key features essential for achieving more accurate simulations are listed.

(G4-SEOPTIM): A GEANT4 application for shielded enclosure, designing and shielding optimizing: The case of a new Moroccan shielded enclosure

PurposeThis study aims to develop and validate a Geant4 simulation application using the latest G4RadioactiveDecayPhysics v5.1 library to optimize the shielding design of a Moroccan shielded enclosure. The goal is to ensure effective radiation protection by comparing simulation results with initial geometric calculations based on the attenuation law (Beer-Lambert Law) and implementing design optimizations to enhance safety and reduce costs. MethodsThe study began with a prototype design based on linear attenuation calculations, which were costly and offered limited patient safety. Using the Geant4 Monte Carlo toolkit, we simulated the decay of a Fluorine-18 source within the shielded enclosure to evaluate dose rate distributions. The simulation's accuracy was validated through comparison with experimental measurements, and the results informed the geometric optimization of the shielding enclosure. ResultsThe Geant4 simulations demonstrated that the current shielding design effectively reduces radiation doses to acceptable levels. However, the simulations also identified opportunities for further optimization of the enclosure's geometry, allowing for more precise and efficient use of shielding materials while maintaining safety standards. ConclusionThe study confirms the utility of Geant4 for optimizing radiation shielding designs. While the initial dimensions provided adequate protection, the simulation enabled more precise geometric optimization. This approach not only enhances radiation protection but also informs the design and construction of more efficient and cost-effective shielding enclosures. The adjustments made to the enclosure's faces significantly improved radiation protection, reducing the dose rate surrounding the shielded enclosure to acceptable levels.

A Comparison of Free and Mapped Meshes for Static Structural Analysis

Abstract This study addresses the challenge faced by Finite Element Analysts when choosing between free and mapped meshes, especially in terms of convergence stability and solution accuracy. The investigation focuses on 3D solid models under static structural loading, analyzed using Ansys® and MSC Patran®. Both free and mapped mesh types, employing equivalent 3D solid elements, are used to assess an aircraft structural component under design load conditions, with fixed boundaries. For free meshes, Tet10 elements in Patran (equivalent to Solid 72 in Ansys) are used, whereas for mapped meshes, CPENTA / CHEXA elements in Patran (equivalent to Wed6 / Hex8 in Ansys) are employed. Mesh convergence studies ensure that discretization does not affect the numerical solution. Notably, a significant stress increase is observed with successive refinement of free meshes, while mapped meshes achieve mesh independence at coarser refinement levels. Comparison of fringe plots indicates the same location for maximum deformation and equivalent stress in both free and mapped mesh models. The findings demonstrate that free meshes tend to underpredict maximum deformation and equivalent stress compared to mapped meshes, with both meshes showing deformation and stress at consistent locations. The findings underscore the importance of carefully choosing the appropriate mesh type, particularly when analyzing critical structural components, to ensure reliability and accuracy in FEA simulations.

Accurate carbon structure for prediction of reaction pathway during bio-coal production using torrefaction

The structural parameters of carbon were accurately determined through correction by employing a linear correlation method. Further, the nuclear Overhauser effect (NOE) was reduced in solid 13C-nuclear magnetic resonance spectra using a solid cross-polarization/magic angle spinning (CP/MAS) probe and the total suppression of sidebands sequence (TOSS). The reaction pathway during torrefaction was inferred from analysis of the accurate bond behavior and product distribution. The results show that torrefaction has a significant influence on the structural evolution of biomass. After correction, the relative deviations in the H/C ratio and aromaticity of the carbon structure decreased below 20 %. During torrefaction, the aliphatic carbon bonds were cleaved and aromatic carbon bonds were formed by dehydration, deoxygenation, oligomerization, aromatization, and Diels-Alder reaction. Torrefaction of biomass is divided into three stages. The first stage occurs below 220 °C, with disruption of the hydrogen bonds, a decrease in the number of Cal-O bonds, and the release of some CO2, CO, and furaldehyde. The second stage proceeds in the 220–260 °C range, where β-O-α bonds and glycoside bonds are broken, with the generation of ketones, furan, phenols, CO, and CO2. In the third stage between 260 and 300 °C, Cal-O and Cal-Cal bonds are broken. Bio-coal is composed of monomers of C20H14O3 with two aromatic rings linked by one aromatic ring. This significant, fundamental study enables accurate calculation and simulations for optimizing the industrial utilization of biomass.

Wind tunnel testing and modelling of a rod-airfoil setup: validation and 3D acoustic imaging

This work revisits the rod-airfoil benchmark experiment from Jacob et al. (2004) with the aim of performing a detailed numerical validation in the nearfield and far field as well as to perform 3D acoustic imaging. The setup consists of a rod near the leading edge of a NACA-0012 airfoil and is placed in a semi-open wind tunnel in anechoic conditions. In addition to a far-field microphone array, the setup is equipped with two planar microphone arrays as well as wall-mounted microphones on the closed wind tunnel section and on the airfoil. The setup is modelled using a second-order finite volume method, and particular attention is devoted to including installation effects and sensor response properties in order to guarantee simulation accuracy. Validation examples are provided, including single microphone spectra as well as the acoustic field reconstructed on the test object by means of 3D acoustic imaging using the planar microphone arrays. Finally, the experimentally-validated numerical model is used as a means to gain further insight into the tested object. For instance, the model allows to separate acoustical and turbulent effects present in the sensors located within the flow section.