Dynamic Simulation Research Articles

Study on the wear performance of 304 stainless steel aerospace joint bearings

In order to investigate the influence of surface micro-texture on the oil film carrying capacity, a theoretical model of dynamic pressure lubrication is constructed based on CFD, and dynamic pressure lubrication simulation and friction and wear experimental research are used to analyse the influence of speed and load on the friction behaviour of the bearing pair, and the wear performance of the specimen is evaluated by means of the surface morphology and friction coefficient. The results show that the carrying capacity of the oil film on the textured surface is relatively large compared with that of the non-textured surface, showing regular fluctuations, and that the pressure values of turbulent flow are greater than those of laminar flow. As the rotational speed increases, the cavitation effect becomes more and more obvious, and the carrying capacity of the oil film increases. The smaller the thickness of the surface oil film, the higher the load carrying capacity and the lower the degree of wear; The surfaces of the textured specimens showed the best friction reduction and anti-wear properties, followed by the smooth surfaces and the worst rough surfaces. With the increase of rotational speed, the friction coefficient tends to decrease. When the rotational speed is 0.4 m s−1, the wear of the textured surface is reduced. With the increase of load, the thickness of the formed oil film decreases, the friction coefficient decreases, and the anti-friction effect of the textured surface increases. This indicates that the surface texure treatment of 304 stainless steel, and the selection of appropriate working condition parameters can effectively reduce wear during the friction process, and improve the wear resistance of bearings.

Transformer fault identification based on GWO-optimized Dual-channel M-A method.

In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. First, a Dual-channel model is constructed by combining the AM (Attention Mechanism) and MLP. Subsequently, the GWO algorithm is used to optimize the number and the nodes of the hidden layer in the Dual-channel MLP-Attention model. Typical transformer faults are simulated using DDRTS (Digital Dynamic Real-Time Simulator) system. Experiments showed that the GWO- optimized method has an accuracy rate of 95.3%-96.7% in identifying the transformer faults. Compared with BP, SVM, MLP, and single-channel M-A models, the proposed method improved the accuracy by14.1%, 9.6%, 9.3%, and 3.3% respectively. This result indicates the rationality and effectiveness of the proposed method in transformer fault identification.

Design, synthesis, molecular dynamics and gene silencing studies of novel therapeutic HIF-1α siRNAs in hypoxic cancer cells

Hypoxia inducible factors (HIFs) are heterodimeric proteins that belong to a small group of transcription factors, which mainly regulates transcription of genes under hypoxic conditions. Particularly, oxygen sensing subunit of HIF-1α is a predominant subtype that heterodimerizes with oxygen-independent HIF-1β subunit, to trigger the transcription of hypoxia responsive genes. Due to poor supply of blood and rapid division of cancerous cells, tumor microenvironment exhibits low oxygen condition and therefore increased levels of HIF-1α. One of the promising therapeutic strategies to cancer is modulation of HIF-1α signaling pathway. Small interfering RNA (siRNA) mediated downregulation of HIF-1α has been reported to prevent growth and progression of various types of cancer and holds great promise in the cancer treatment. In this study, computational approaches were used to design potential siRNAs targeting HIF-1α and investigate their interaction with the human argonaute-2 (hAgo2). Molecular dynamic simulation of HIF-1α siRNAs-hAgo2 complexes revealed key interactions required for the efficient binding of guide strand to hAgo2 protein. Two siRNAs (S2 and S5) exhibiting strong binding with hAgo2 were further considered. Subsequently, we transfected the MCF-7 cell line with both standard HIF-1α and our designed siRNAs (S2 and S5). Following transfection, translation changes in the MCF-7 cells were assessed through western blotting. S2 and S5 efficiently reduced the expression of HIF-1α in hypoxic conditions. The aim of the present study is to understand the siRNA-hAgo2 interaction. It is also focused on the desiging of effective siRNA against HIF-1α.

Design, synthesis, QSAR modelling and molecular dynamic simulations of N-tosyl-indole hybrid thiosemicarbazones as competitive tyrosinase inhibitors

Tyrosinase is an enzyme crucial for the progression of melanogenesis. Immoderate production of melanin may be the cause of hyperpigmentation and darkening leading to skin diseases. Tyrosinase is the most researched target for suppressing melanogenesis since it catalyzes the rate-limiting stage of melanin production. Thiosemicarbazones have been reported to possess strong inhibition capability against tyrosinase. We have designed and synthesized eighteen N-tosyl substituted indole-based thiosemicarbazones as competitive tyrosinase inhibitors in the current work. All the compounds exhibited outstanding to good potency with half maximal inhibitory concentration in the range of 6.40 ± 0.21 µM to 61.84 ± 1.47 µM. The compound 5r displayed the top-tier inhibition amongst the entire series with IC50 = 6.40 ± 0.21 µM. Compounds, 5q and 5r exhibited competitive inhibitions in concentration dependent manner with Ki = 3.42 ± 0.03 and 10.25 ± 0.08 µM respectively. The binding mode of 5r was evaluated through in silico molecular dynamics simulations and molecular docking, while ADME assessment studies predicted the drug-like characteristics of the derivatives. The newly synthesized derivatives may serve as a structural guide for designing and developing novel tyrosinase inhibitors.

Characterization of mitochondrial DNA mutations in colorectal cancer progression by in silico approach and use as potential biomarkers for diagnosis and prognosis

BackgroundMitochondrial DNA variants are significant contributors to cancer progression, as evidenced by numerous findings. This study focuses on characterizing mitochondrial DNA mutations in colorectal cancer progression and their potential as biomarkers.MethodologyNext generation sequencing technology was employed to analyze mitochondrial DNA variants in tumor and adjacent normal tissues from 25 patients with colon/rectal cancer. In silico prediction tools (SIFT, Polyphen2, Mutation Assessor, and SNP&GO) were utilized to assess the pathogenicity of these variants. Additionally, homology modeling of mutated protein structures was conducted, and molecular dynamic simulations were performed to assess the impact of mutation on protein function.ResultsEighteen variants were identified across most tumor tissue samples, located in genes from Complex I, IV, and V. Among the identified variants, the V302M and S461 mutations in the MT-ND5 gene and L137F and L220P mutations in the ATP6 gene were predicted to be deleterious, potentially affecting protein function. 3D structural analysis of both wild-type and mutant proteins of MT-ND5 revealed changes in flexibility for the V302M and S461G mutations. The MT-ATP6 mutations L135F and L220P disrupt the interactions with surrounding residues and affect the overall function of protein. Further changes in protein dynamics of the mutated proteins by molecular dynamic simulations also indicate the effects; the mutations have on protein function.ConclusionMT-ND5 and MT-ATP6 variants could serve as potential biomarkers and drug targets in colorectal cancer. This study underscores the significance of mitochondrial DNA variants in cancer progression.

Defining a maximum heat release rate probability distribution function for design fires in sprinkler‐protected residential buildings

AbstractIn fire safety engineering analysis of sprinkler‐protected residential buildings, the maximum heat release rate is a key parameter requiring consideration. Several documents provide advice for estimating the heat release rate of a sprinkler‐controlled fire, with a prevailing suggestion that it is fixed upon activation of the first sprinkler. When carrying out deterministic analysis, this requires the engineer to assume fixed fire parameters and consider that sprinklers limit fire growth. To explore these assumptions, the study uses three deterministic models to estimate a sprinkler‐controlled maximum heat release rate for a representative apartment layout. The models include Alpert's correlation, a B‐RISK zone model and a computational fluid dynamics model in the Fire Dynamics Simulator. These deterministic models are compared to a probabilistic model in B‐RISK, where Monte Carlo simulations are used to generate a range of maximum heat release rates from distribution functions for fire and sprinkler properties. An output distribution function is generated with a mean of 296.6 kW and a standard deviation of 503.8 kW, with a lognormal distribution (μ = 5.014, σ = 1.165) estimated as a best‐fit. The deterministic models are estimated to sit in the 92–98 percentile range of this function, indicating that common deterministic assumptions are reasonably conservative. The article concludes with suggesting that, for deterministic analysis, a percentile between the 80th and 99th (340–2640 kW) could be qualitatively selected based on the design objectives, building situation and relative consequence of a fire. Further research is needed to establish guidelines for selecting appropriate percentiles across various building scenarios.

Deciphering the 4',7-Dihydroxy-3'-Methylflavone from Boerhavia, Agonist/Antagonist Interactions Against 5-HT2 Receptors using Homology Modeling, Molecular Docking, and Dynamic Simulation Studies.

Seizures, depression, and anxiety are neurological disorders that affected innumerable people worldwide. Recent research has revealed that targeting 5-hydroxytryptamine 2 (5-HT2) receptors can help suppress these conditions. An in-depth literature study has identified that phytocompounds from the Boerhavia genus could reduce seizures. Therefore, homology models of 5-HT2 receptors were generated and validated using techniques such as the alignment of amino acid sequences and the Ramachandran plot. Later, a comparison of modeled structures was made with a non-redundant set of PDB structures. The pharmacokinetics, drug-likeness, blood-brain barrier (BBB) permeability, and Lipinski's rule of five shed light on 22 phytocompounds, which are the potential candidates for molecular docking among 127 Boerhavia's bioactive. Notably, molecular docking analysis revealed 4',7-dihydroxy-3'-methylflavone as the most potent lead compound, which has a strong binding affinity to all modeled receptors. Additionally, with a remarkably high docking score of -9.1 kcal/mol, 4',7-dihydroxy-3'-methylflavone showed promising interactions, particularly with 5-HT2A receptor, as seen from the RMSD, SASA, Rg, and number of hydrogen bonds during 100 ns molecular dynamic (MD) simulation. Principal component analysis (PCA) and Molecular Mechanics-Poisson-Boltzmann Surface Area (MM-PBSA) further confirmed that 4',7-dihydroxy-3'-methylflavone is the best novel phytocompound in Boerhavia genus for 5-HT2 receptor as agonist/antagonist activity against seizures.

Evaluating the Effect of Adaptive Reuse in the Energy Performance of Historic Buildings: A Case Study from Türkiye

The building sector accounts for 30% to 40% of total energy consumption, and historic buildings play an important role in this proportion. Historical buildings that do not meet the required comfort conditions for the residents are adaptively reused, with various revisions. Recognizing the energy design of a historical building in its original condition and comparing the current situation can help create future solutions. This study examines the changes that a historic house in a hot climate zone in Türkiye experiences, from its original state up until the current situation. Energy analyses of the pre- and post-restoration situation are carried out, and the effect of adaptive reuse decisions on the energy performance of the building is investigated. A dynamic thermal simulation created with DesignBuilder was used to identify the energy use, carbon emissions, and thermal comfort. TM59 adaptive thermal comfort was used for the pre-restoration and the Fanger model for the post-restoration phase. This building, which was repurposed from a three-block residence, consists of a four-block hotel. Although the preservation of its original value is at the forefront, various structural changes were observed. The analysis demonstrates a higher occurrence of discomfort hours during summer compared to winter, consistent across both phases. Furthermore, energy consumption increased significantly, predominantly for heating, representing a doubling of energy use during the post-restoration phase. This is attributed to the building’s conversion into a hotel and the use of mechanical systems. Future research is required to develop strategies to reduce the energy consumption, carbon emissions, and discomfort hours while maintaining the value of the historic building and its materials.

Data-Driven Approaches for State-of-Charge Estimation in Battery Electric Vehicles Using Machine and Deep Learning Techniques

One of the most important functions of the battery management system (BMS) in battery electric vehicle (BEV) applications is to estimate the state of charge (SOC). In this study, several machine and deep learning techniques, such as linear regression, support vector regressors (SVRs), k-nearest neighbor, random forest, extra trees regressor, extreme gradient boosting, random forest combined with gradient boosting, artificial neural networks (ANNs), convolutional neural networks, and long short-term memory (LSTM) networks, are investigated to develop a modeling framework for SOC estimation. The purpose of this study is to improve overall battery performance by examining how BEV operation affects battery deterioration. By using dynamic response simulation of lithium battery electric vehicles (BEVs) and lithium battery packs (LIBs), the proposed research provides realistic training data, enabling more accurate prediction of SOC using data-driven methods, which will have a crucial and effective impact on the safe operation of electric vehicles. The paper evaluates the performance of machine and deep learning algorithms using various metrics, including the R2 Score, median absolute error, mean square error, mean absolute error, and max error. All the simulation tests were performed using MATLAB 2023, Anaconda platform, and COMSOL Multiphysics.

Anti-Inflammatory Humulene-Type Sesquiterpenoids from Asteriscus Graveolens

Objectives: Inflammation is the initial physiological reaction of the immune system to infection or irritation, leading significant risk factors for several forms of cancer. The genus Asteriscus has been observed to possess a notable abundance of sesquiterpenes with anti-inflammatory properties. This study was designed to assess the anti-inflammatory activity of the sesquiterpenoids isolated from Asteriscus graveolens. Methods: The organic extract of the Asteraceae plant A. graveolens was subjected to different chromatographic and spectroscopic techniques for isolation, purification, and identification of sesquiterpenoid contents. The isolated compounds were screened for anti-inflammatory activities in two animal models: rat paw edema and rat ear edema. Histopathological examinations as well as biochemical markers of inflammation were assessed. This was followed by in silico screening for anti-inflammatory activity. Results: Four known sesquiterpenoids were isolated from A. graveolens, including two humulene derivatives, namely, 9-oxohumula-4-en-6,15-olide (1), and 9-oxohumula-1(10)(Z),4,7(E)-trien-6,15-olide (2) and two bisabolene derivatives, identified as bisabola-2,10-dien-1-one (3) and 6- hydroxybisabola-2,10-dien-1-one (4) described. In the rat paw edema model, compound 2 showed highest activity in preventing formation carrageenan-induced paw edema. This was confirmed by histopathological examinations that indicated partial preservation of the epidermal and dermal layers. Further, the compound significantly inhibited cyclooxygenase-2 (COX-2) and tumor necrosis factor-α (TNF-α) release. In the croton oil indued rat ear edema, compounds 2 and 4 significantly inhibited ear edema and protected against histopathological alterations. This was associated with prevention of myeloperoxidase (MPO) concentration in ear tissues. Molecular docking and molecular dynamic simulation indicated the affinity and docking stability of compounds 1-4 to the selected inflammatory protein. Conclusion: Phytochemical investigation of A. graveolens resulted in the isolation and characterization of four sesquiterpenes. In particular, compound 2 showed potent anti-inflammatory activity in carrageenan rat paw edema and croton oil ear edema.

Dynamic Simulation of Carbon Emission Peak in City-Scale Building Sector: A Life-Cycle Approach Based on LEAP-SD Model

Systematically predicting carbon emissions in the building sector is crucial for formulating effective policies and plans. However, the timing and potential peak emissions from urban buildings remain unclear. This research integrates socio-economic, urban planning, building technology, and energy consumption factors to develop a LEAP-SD model using Shenzhen as a case study. The model considers the interrelationship between socio-economic development and energy consumption, providing more realistic scenario simulations to predict changes in carbon emissions within the urban building sector. The study investigates potential emission peaks and peak times of buildings under different population and building area development scenarios. The results indicate that achieving carbon peaking by 2030 is challenging under a business as usual (BAU) scenario. However, a 10% greater reduction in energy intensity compared to BAU could result in peaking around 2030. The simulation analysis highlights the significant impact of factors such as population growth rate, per capita residential building area, and energy consumption per unit building area and the need for a comprehensive analysis. It provides more realistic scenario simulations that not only enhance theories and models for predicting carbon emissions but also offer valuable insights for policymakers in establishing effective reduction targets and strategies.

Moisture dynamics during high‐load fluctuations in transformers: Localised accumulation and interfacial transfer within oil/pressboard insulation

AbstractPower systems grapple with the challenges of high load rates and intermittent new energy sources integration. Transformers, as vital equipment, employ oil/pressboard (oil/PB) insulation. Uneven moisture distribution in this insulation can jeopardise safety thresholds, necessitating precise moisture assessment for grid stability. A novel mathematical model, adsorption–desorption and porous media moisture transfer (ADP‐MoT), is presented. This model incorporates adsorption and desorption processes within the porous pressboard, enabling a description of the dynamic moisture transfer between the oil and pressboard. Using this mathematical model, simulations for moisture dynamics were performed on a 750‐kV transformer across four typical days. The results indicate that temperature fluctuations are the primary driving factor for moisture migration at the oil/PB interface. Convection and diffusion contribute to moisture movement towards cooler regions. Fluid properties and structural characteristics induce a distinctive streamline‐shaped moisture flow within horizontal oil channels, with localised moisture accumulation in specific areas. Moreover, the analysis of 96 transient results uncovers potential free‐state moisture formation during severe conditions, underscoring the importance of monitoring the pressboard at winding bases during high load fluctuations. In conclusion, this study significantly contributes to scientifically identifying and addressing risks tied to new energy sources integration in power systems.

Simulating unsteady flows on a superconducting quantum processor

Recent advancements of quantum technologies have triggered tremendous interest in exploring practical quantum advantage. The simulation of fluid dynamics, a highly challenging problem in classical physics but vital for practical applications, emerges as a potential direction. Here, we report an experiment on the digital simulation of unsteady flows with a superconducting quantum processor. The quantum algorithm is based on the Hamiltonian simulation using the hydrodynamic formulation of the Schrödinger equation. With the median fidelities of 99.97% and 99.67% for parallel single- and two-qubit gates respectively, we simulate the dynamics of a two-dimensional (2D) compressible diverging flow and a 2D decaying vortex with ten qubits. Note that the former case is an inviscid potential flow, and the latter one is an artificial vortical flow with an external body force. The experimental results well capture the temporal evolution of averaged density and momentum profiles, and qualitatively reproduce spatial flow fields with moderate noises. This work demonstrates the potential of quantum computing in simulating more complex flows, such as turbulence, for practical applications.

A novel simulation of space charge decay dynamics after removing the voltage in epoxy resin composites

Abstract Epoxy resin serves as a critical insulating component in ultra-high voltage dry direct current bushings. However, the accumulation of space charges within the epoxy resin, a byproduct of charge mobility, poses a significant risk to the reliability and operational safety of bushings. Conventional space charge attenuation models, especially after voltage removal, have limited use in simulations aimed at understanding this phenomenon. This study introduces an improved model integrating the bipolar charge transport mechanism with space charge decay based on the hopping conduction mechanism and Schottky’s theorem, establishes a theoretical framework for predicting the space charge behavior following voltage removal, and conducts a simulation to investigate the decay process within the internal structure of epoxy resin and measure the residual charges after voltage removal using the pulsed electro-acoustic method. The experimental data validate the accuracy of the proposed model and theoretical assumptions. The findings show that the remaining negative charges after voltage removal are not enhanced by the field enhancement; the anodic positive and cathodic positive charges are distributed in two-segment discontinuous traps, whereas the negative charges are distributed in one-segment traps. The model identifies two distinct trapping sites for anodic and cathodic positive charges, and one trapping site for negative charges. After voltage removal, when the field strength exceeded 40 kV mm−1, positive charges exist near the upper and lower electrodes, and negative charges exist near the center of the specimen. The consistency between the simulated predictions and experimental data proves the effectiveness of the proposed model in accurately simulating the space charge decay in epoxy materials after voltage removal.

Effect of Natural Inhibitors on the Corrosion Properties of Grade 2 Titanium Alloy

This study investigates the effects of natural inhibitors (pomegranate, algae, and tomato extracts) on the corrosion resistance of titanium (grade 2). To deepen understanding the inhibition mechanism, Molecular Dynamic (MD) and Monte Carlo (MC) simulations were employed to analyze adsorption behaviors and identify optimal adsorption sites on titanium oxide (TiO2) surfaces for compounds within the inhibitors. Results indicate non-flat adsorption orientations, with pomegranate peel extract components showing superior inhibition capabilities, attributed to the formation of strong O-H chemical bonds with the TiO2 surface. In the experimental part of the study Electrochemical Impedance Spectroscopy (EIS) and Potentiodynamic Polarization (PDP) were conducted. Two electrolytes were tested: a solution 3.5% NaCl and a solution 0.5 M NaOH. All the tests were performed with 5% of inhibitor and with the reference solution. Also, inhibition efficiency was calculated on the base of PDP tests. The study found that pomegranate extract can act as a good corrosion inhibitor for titanium alloy in aqueous solutions 0.5 M NaOH. This was demonstrated by the increase in the corrosion potential and impedance modulus and decrease in the corrosion current density after the addition of pomegranate extract to the solution. However, in a 3.5% NaCl solution, the efficacy of pomegranate extract was less pronounced, probably due to the high aggressivity of the electrolyte. Tomato and algae extract have instead shown very low inhibition effects in all the tested conditions.

Thermoelectric transport in molecular crystals driven by gradients of thermal electronic disorder.

Thermoelectric materials convert a temperature gradient into a voltage. This phenomenon is relatively well understood for inorganic materials but much less so for organic semiconductors (OSs). These materials present a challenge because the strong thermal fluctuations of electronic coupling between the molecules result in partially delocalized charge carriers that cannot be treated with traditional theories for thermoelectricity. Here, we develop a quantum dynamical simulation approach revealing in atomistic detail how the charge carrier wave function moves along a temperature gradient in an organic molecular crystal. We find that the wave function propagates from hot to cold in agreement with the experiment, and we obtain a Seebeck coefficient in good agreement with experimental measurements that are also reported in this work. Detailed analysis reveals that gradients in thermal electronic disorder play an important role in determining the magnitude of the Seebeck coefficient, opening unexplored avenues for the design of OSs with improved Seebeck coefficients.

Role of mechanical stress localizations on the radiation hardness of AlGaN/GaN high electron mobility transistors

Abstract Multi-material, multi-layered systems such as AlGaN/GaN high electron mobility transistor (HEMTs) contain residual mechanical stresses that arise from sharp contrasts in device geometry and materials parameters. These stresses, which can be either tensile or compressive, are difficult to detect and eliminate because of their highly localized nature. We propose that their high stored internal energy make potential sites for defect nucleation sites under radiation, particularly if their locations coincide with the electrically sensitive regions of a transistor. In this study, we validate this hypothesis with molecular dynamic simulation and experiments exposing both pristine and annealed HEMTS to 2.8 MeV Au+3 irradiation. Our unique annealing process uses mechanical momentum of electrons, also known as the electron wind force (EWF) to mitigate the residual stress at room temperature. High-resolution transmission electron microscopy (TEM) and cathodoluminescence spectra reveal the reduction of point defects and dislocations near the two-dimensional electron gas region of EWF-treated devices compared to pristine devices. The EWF-treated HEMTs showed relatively higher resilience with approximately 10% less degradation of drain saturation current and ON-resistance and 5% less degradation of peak transconductance. Both mobility and carrier concentration of the EWF-treated devices were less impacted compared to the pristine devices. Our results suggest that the lower density of nanoscale stress localization contributed to the improved radiation tolerance of the EWF-treated devices. Intriguingly, the EWF is found to modulate the defect distribution by moving the defects to electrically less sensitive regions in the form of dislocation networks, which act as sinks for the radiation induced defects and this assisted faster dynamic annealing.

Performance analysis of solar-assisted ground source heat pump in severe cold regions

ABSTRACT Long-term operation of a ground source heat pump (GSHP) in severe cold regions leads to a gradual decrease in subsurface soil temperature, affecting system performance. This paper proposes a solar assisted ground source heat pump (SAGSHP) system consisting of solar photovoltaic thermal (PV/T) and GSHP. Through TRNSYS software, the system was analyzed for 10 years of dynamic simulation in a severe cold region. The results are listed below: (1) The SAGSHP system is capable of effectively lessening the maximal temperature of photovoltaic (PV) modules in Changchun, Shenyang, and Harbin, China, by 21.73%, 13.67%, and 19.10%, respectively. The power generation efficiency of PV modules in these three locations can be maintained at about 22% year-round. (2) After ten years of operation, the coefficients of performance (COP) of the heat pumps have increased by 5.70%, 6.80%, and 5.01%, respectively, relative to the first year, showing good stability. (3) The soil temperatures at all three locations were stabilized during the ten years of operation. This study provides a theoretical basis for devising and installing SAGSHP in severe cold regions.

Informal settlements ablaze: decoding the combustible nature of building materials used in Bangladesh through experiments and numerical analysis

ABSTRACT Fire outbreaks in informal settlements pose severe threats to residents and their properties. Despite the frequent occurrence of fire events in Bangladesh, detailed studies on fire propagation behaviour remain limited. This study addresses this critical issue by comprehensive investigations into the ignitability and burning behaviour of different materials such as cardboard, polyurethane foam, plastic bags, wood, and structural timber that are commonly found in informal settlements. Additionally, an advanced numerical model based on the finite volume method was developed in Fire Dynamics Simulator and then employed to accurately predict the fire-reaction properties of materials under the cone calorimeter environment. The results revealed that cardboard ignites quickly, burns moderately, and does not produce flaming droplets or ignite the filter paper. PU foam burns vigorously, with a high burning rate, and emits dense black smoke and a toxic odour. Plastic bags ignite rapidly, burn intensely, and are greatly influenced by the presence of airflow. The numerical model successfully quantified fire-reaction properties such as ignition time, heat release rate (HRR), and flame spread characteristics. Notably, wood and structural timber demonstrate a distinct combustion pattern with a sharp HRR peak, while PU foam exhibits the highest peak HRR values followed by timber masonite.

Immersed boundary method for dynamic simulation of polarizable colloids of arbitrary shape in explicit ion electrolytes.

We develop a computational method for modeling electrostatic interactions of arbitrarily shaped, polarizable objects on colloidal length scales, including colloids/nanoparticles, polymers, and surfactants, dispersed in explicit ion electrolytes and nonionic solvents. Our method computes the nonuniform polarization charge distribution induced in a colloidal particle by both externally applied electric fields and local electric fields arising from other charged objects in the dispersion. This leads to expressions for electrostatic energies, forces, and torques that enable efficient molecular dynamics and Brownian dynamics simulations of colloidal dispersions in electrolytes, which can be harnessed to accurately predict structural and transport properties. We describe an implementation in which colloidal particles are modeled as rigid composites of small spherical beads that tessellate the surface of the particle. The electrostatics calculations are accelerated using a spectrally accurate particle-mesh-Ewald technique implemented on a graphics processing unit and regularized such that the electrostatic calculations are well-defined even for overlapping bodies. We illustrate the effectiveness of this approach with a comprehensive set of calculations: the induced dipole moments and forces for individual, paired, and lattice configurations of spherical colloids in an electric field; the induced dipole moment and torque for anisotropic particles subjected to an electric field; the equilibrium ion distribution in the double layer surrounding charged colloids; the dynamics of charged colloids; and the behavior of ions in the double layer of a polarizable colloid under the influence of an electric field.