Solid Mechanics Research Articles

Zero-Strain Sodium Nickel Ferrocyanide as Cathode Material for Sodium-Ion Batteries with Ultra-Long Lifespan.

Prussian blue analogues are recognized as one of the most promising cathode materials for sodium-ion batteries (SIBs) owing to the open 3D framework structure with large interstitial sites and developed Na-ion diffusion channels. However, high content of anion vacancy and poor structural stability have hampered the prospect of their application. In this work, sodium nickel ferrocyanide (Na1.34Ni[Fe(CN)6]0.92, NNHCF) is proposed as cathode material for SIBs. N-coordinated Ni-ion can boost NNHCF to possess less Fe[(CN)6]4- defect, low Na-ion migration barrier, and more negative formation energy compared with Na0.91Cu[Fe(CN)6]0.77 (NCHCF), thus exhibiting more active sites, fast electrochemical kinetics behavior and great structure stability. It is confirmed that NNHCF undergoes a solid solution mechanism without phase evolution for reversible Na-ion intercalation/deintercalation, employing Fe associated with C atom as redox center for charge compensation. Therefore, NNHCF contributes a high initial energy density of 180.94 Wh·g-1 at 10 mA·g-1, excellent rate capability, superior cycling stability with ultra-long lifespan of 13000 cycles, and low fading rate of 0.0027% per cycle at 500 mA·g-1. This work sheds light on the construction of low-defect PBA cathodes with outstanding dynamics and stability.

Treatment of inelastic material models within a dynamic ALE formulation for structures subjected to moving loads

AbstractThis article showcases the development of a dynamic Arbitrary Lagrangian Eulerian (ALE) formulation to account for inelastic material models within a finite element framework. Such a formulation is commonly utilized in research domains like fluid mechanics, fluid‐structure interaction, quasi static remeshing techniques, and quasi static load movement. The work at hand describes the application of the ALE formulation to efficiently analyse structures subjected to moving loads in the field of transient inelastic solid mechanics. In particular, structures such as pavements, gantry crane girders etc., which are subjected to moving loads, can be numerically simulated, and their transient response in the relevant region around the load can be obtained without relying on moving loads. The focus of this article is to facilitate the treatment of history variables stemming from inelastic material models. Of particular interest is the advection procedure required to transport the history variables through the mesh, as the material appears to flow through it. The mathematical framework necessary to treat this advection process is described in detail, considering a nonlinear viscoelastic material model on a neo‐Hookean base at finite deformations. Then, four methods for numerically achieving the advection are implemented within a transient finite element ALE formulation. These methods are compared against each other, and additionally with the conventional Lagrangian method for validation. The results demonstrate satisfactory agreement with conventional simulation methods, while offering a significant improvement in terms of computation speed. With the work at hand, the dynamic response of inelastic materials subjected to moving loads can be numerically simulated in a computationally efficient manner.

Directional Transport in Hierarchically Aligned ZSM-5 Zeolites with High Catalytic Activity.

Zeolites, the most technically important crystalline microporous materials, are indispensable cornerstones of chemical engineering because of their remarkable catalytic properties and adsorption capabilities. Numerous studies have demonstrated that the hierarchical engineering of zeolites can maximize accessible active sites and improve mass transport, which significantly decreases the internal diffusion limits to achieve the desired performance. However, the construction of hierarchical zeolites with ordered alignments and size-controlled substructures in a convenient way is highly challenging. Herein, we develop a facile procedure using two common structure-directing agents, tetrapropylammonium hydroxide (TPAOH) and tetraethylammonium hydroxide (TEAOH), to synthesize hierarchically aligned ZSM-5 (Hie-ZSM-5) crystals with a-axis alignment substructures of controllable size. The control of the substructure size (α) in the range of 10-60 nm and the corresponding similarity (r = α/β, where β is the size of Hie-ZSM-5) ranging from 0.004 to 0.033 can be tuned by varying the Si/Al ratios (40-120). A systematic investigation of the overall crystallization process, using time-dependent XRD, SEM, TEM, and solid-state magic-angle spinning NMR (13C, 27Al, 29Si) methods, enable us to construct a solid mechanism for the generation of Hie-ZSM-5. Most importantly, directional transport in the unique structures of Hie-ZSM-5 efficiently enhances mass diffusion, as well as catalytic activity and stability. These findings improve our understanding of the zeolite crystallization process and inspire novel methods for the rational design of hierarchical zeolites.

CFD Modeling of HBI/SCRAP Melting in Industrial EAF and the Impact of Charge Layering on Melting Performance

The melting of scrap and hot briquetted iron (HBI) in an AC electric arc furnace (EAF) is simulated by an advanced 3D computational fluid dynamics (CFD) model that captures the arc heating, the scrap/HBI melting process, and the solid collapse mechanisms. The CFD model is used to simulate a scenario where charge layering and EAF power profiles are provided by a real EAF operation. CFD simulation of the EAF operation shows proper prediction of the charge melting when compared with standard industry practice. Namely, the CFD model predicts a 32.5%/67.5% ratio of solid/liquid steel at the beginning of refining, which approaches the 30%/70% ratio used in standard practice. Based on this prediction, the melting rate in the CFD results differs by 8.3% from actual EAF operation. The impact of charge layering on melting is also investigated. CFD results show that distributing charge material into a greater number of layers in the first bucket (10 layers as compared to 4) enhances the melting rate by 12%. However, including dense material at the bottom of the furnace deteriorates melting performance, reducing the impact of the number of layers of the charge. The CFD platform can be used to optimize the use of HBI/scrap in real EAF operations and to determine best recipe practices.

Numerical simulation of transient thermal stresses in medium- and high-temperature latent heat storage systems with different fins: Incorporation of experimental stress cracking

Latent heat storage systems play an essential role in energy applications by improving the utilization efficiency and increasing the system flexibility. In this study, a pilot-scale medium-to-high-temperature latent heat storage system was constructed, and experimental heat storage tests were conducted. The temperature distribution of the experimental system was verified through numerical simulations that coupled the physical fields of the fluids, heat transfer, and solid mechanics. Also, the changing dynamic behavior of the stresses in the heat storage process related to the experiments was carefully studied. It was discovered that there were stress concentrations where the heat exchanger tubes touched the casing, with the highest level being over 370.00 MPa. Experimental stress rupture of the shell occurred in the horizontally arranged heat-exchange tubes, whereas vertically arranged tubes significantly reduced the stress at the contact surfaces by 24.70 % according to simulations. Simulation studies on various influencing factors indicated a more significant impact of spiral fins on the system stress. Increasing the preheating temperature by 30 °C reduced stress on the front surface by 109.67 MPa; each 20 °C increase in heating temperature raised the stress by 223.30 MPa, whereas the effect of heat transfer fluid speed was minimal. Regarding the heat-exchange tube dimensions, increasing the height increased the tube body stress by 25.74 MPa, whereas increasing the thickness reduced the stress by 24.20 %. This study comprehensively analyzed the stress dynamics and mitigation strategies of the high-temperature latent heat storage system under various conditions, emphasizing the importance of heat-exchange tube orientation, temperature control, and fin design for optimizing system performance and durability.

Delaying cyclization of polyacrylonitrile by boric acid for sulfurized poly(acrylonitrile) cathode materials

Sulfurized poly(acrylonitrile) (SPAN) has become one of the most promising cathode materials in rechargeable Lithium-Sulfur (Li-S) batteries due to their inhibited polysulfide dissolution, high sulfur utilization and excellent electrochemical performance via unique solid–solid conversion mechanism. However, the sulfur content of SPAN (<50 %) is still one of the significant reasons that restrict the electrochemical performance and practical applicability. In this paper, a small amount of boric acid (HBO) was introduced into the precursor of SPAN cathode materials easily before heat-treating, to increase the sulfur content and improve the electrochemical performance. Meanwhile, the results of first principles calculation suggested that the increase of sulfur content of SPAN was derived from the delayed cyclization of polyacrylonitrile (PAN) by HBO. We also discovered when the additive amount of HBO was 1.5 % of PAN mass, the SPAN cathode material possessed high sulfur content up to 54.24 wt%, and delivered prominent reversible electrochemical performances of 714 mAh/g at 0.2C and 734 mAh/g at 0.1C with high Coulombic efficiency. In summary, we proposed a simple and easy method to improve sulfur content and introduced a new strategy for the design of high-sulfur content and high-performance SPAN cathode materials.

Slowed Singlet Exciton Fission Enhances Triplet Exciton Transport in Select Perylenediimide Crystals.

Singlet fission (SF) materials used in light-harvesting devices must not only efficiently produce spin-triplet excitons but also transport them to an energy acceptor. N,N'-Bis(2-phenylethyl)-3,4,9,10-perylenedicarboximide (EP-PDI) is a promising SF chromophore due to its photostability, large extinction coefficient, and high triplet yield, but the energy transport mechanisms in EP-PDI solids are minimally understood. Herein, we use transient absorption microscopy to directly characterize exciton transport in EP-PDI crystals. We find evidence for singlet-mediated transport in which pairs of triplet excitons undergo triplet fusion (TF), producing spin-singlet excitons that rapidly diffuse. This interchange of singlet and triplet excitons shuttles triplets as far as 205 nm within the first 500 ps after photoexcitation. This enhanced transport comes at a cost, however, as it necessitates favoring triplet recombination and thus requires fine-tuning of SF dynamics to balance triplet yields with triplet transport lengths. Through numerical modeling, we predict tuning the ratio of SF and TF rate constants, kSF/kTF, to between 1.9 and 3.8 allows for an optimized triplet transport length (425-563 nm) with minimal loss (7-10%) in triplet yield. Interestingly, by adjusting the size of EP-PDI crystals, we find that we can subtly tune their crystal structure and thereby alter their SF and TF rates. By slowing SF within small EP-PDI crystals, we are able to boost their triplet transport length by ∼20%. Although counterintuitive, our work suggests slowing SF by introducing moderate structural distortions can be preferential when optimizing triplet exciton transport, provided singlet exciton transport is not significantly hindered.

Physics-Informed Neural Network for Solving a One-Dimensional Solid Mechanics Problem

Our objective in this work is to demonstrate how physics-informed neural networks, a type of deep learning technology, can be utilized to examine the mechanical properties of a helicopter blade. The blade is regarded as a one-dimensional prismatic cantilever beam that is exposed to triangular loading, and comprehending its mechanical behavior is of utmost importance in the aerospace field. PINNs utilize the physical information, including differential equations and boundary conditions, within the loss function of the neural network to approximate the solution. Our approach determines the overall loss by aggregating the losses from the differential equation, boundary conditions, and data. We employed a physics-informed neural network (PINN) and an artificial neural network (ANN) with equivalent hyperparameters to solve a fourth-order differential equation. By comparing the performance of the PINN model against the analytical solution of the equation and the results obtained from the ANN model, we have conclusively shown that the PINN model exhibits superior accuracy, robustness, and computational efficiency when addressing high-order differential equations that govern physics-based problems. In conclusion, the study demonstrates that PINN offers a superior alternative for addressing solid mechanics problems with applications in the aerospace industry.

Continuum Mechanics Applied to the Biomechanics of Motion.

Continuum Mechanics is the discipline that studies the motion and deformation of material bodies, and is at the basis of both Solid Mechanics and Fluid Mechanics. This works aims at highlighting how a basic education in modern Continuum Mechanics can be of fundamental importance not only in the Biomechanics of Tissue, but also in the Biomechanics of Movement. The latter is largely based on Rigid Body Mechanics, which can be considered as a simple particular case of the general theory of Continuum Mechanics. As an example, a straightforward methodology for the extraction of the angular velocity from motion analysis data is illustrated. The method is based on a quantity that is more primitive than the angular velocity: the spin tensor.

Multiscale homogenized constrained mixture model of the bio-chemo-mechanics of soft tissue growth and remodeling.

Constrained mixture models have successfully simulated many cases of growth and remodeling in soft biological tissues. So far, extensions of these models have been proposed to include either intracellular signaling or chemo-mechanical coupling on the organ-scale. However, no version of constrained mixture models currently exists that includes both aspects. Here, we propose such a version that resolves cellular signal processing by a set of logic-gated ordinary differential equations and captures chemo-mechanical interactions between cells by coupling a reaction-diffusion equation with the equations of nonlinear continuum mechanics. To demonstrate the potential of the model, we present 2 case studies within vascular solid mechanics: (i) the influence of angiotensin II on aortic growth and remodeling and (ii) the effect of communication between endothelial and intramural arterial cells via nitric oxide and endothelin-1.

Stress Analysis of Radial Compression Disk Based on MATLAB

Elastic mechanics is an important branch of solid mechanics, mainly studies the deformation and internal force of elastic objects under the action of external forces and other external factors, also known as elastic theory. The study object of elasticity is elastomer. The detailed theoretical structure helps us solve more practical engineering problems. We used Matlab software in the data simulation for visualization processing. On the basis of the study of elasticity, this paper explores the stress distribution of the uniform ideal elastic body to the radial compression disk model, and observes the change of the stress of the radial compression disk when the external pressure changes gradually. The expressions of the corresponding stress components , and are obtained by using the theory of normal concentrated force on the boundary of a half plane body. The stress solutions considering the thickness t of the disk are derived. Finally, the drawing software in Matlab software is used to visualize the theoretical derivation results in order to intuitively feel the change of stress. After the data simulation, the data simulation results are compared with the stress analysis results derived from the theoretical deduction, and the conclusion is drawn.

Effect of a gunite lining on the stability of salt caverns in bedded formations for hydrogen storage

In this paper, a novel methodology to improve the structural behaviour and durability of bedded salt caverns for hydrogen storage is proposed. The suggested technology consists in applying a gunite lining over the whole cavern surface by means of a pneumatic air blowing. This continuous flow projected at high speed onto the cavern surface produces a self-compacted gunite facing. The effect of adding a gunite lining on the structural performance of a bedded salt cavern is analysed. The nonlinear finite element method is then applied to solve the inherent nonlinear solid mechanics problem. It is shown that reinforcing salt caverns with a gunite lining improves the cavern behaviour, specially in the case of caverns located within a horizontal salt stratum confined between other strata. When dealing with these salt formations, the stratum geometry limits the cavern height. In general, wider caverns that exhibit larger displacements are required to achieve a huge storage capacity. Moreover, these caverns can be located at a considerable depth, where the temperature has an important role on the creep deformation process. Therefore, the proposition of stabilization techniques is required to ensure both their structural integrity and the ground subsidence. This technology allows the safe exploitation of salt caverns located at bedded-type stratified horizontal salt formations.

A review of graph neural network applications in mechanics-related domains

Mechanics-related tasks often present unique challenges in achieving accurate geometric and physical representations, particularly for non-uniform structures. Graph neural networks (GNNs) have emerged as a promising tool to tackle these challenges by adeptly learning from graph data with irregular underlying structures. Consequently, recent years have witnessed a surge in complex mechanics-related applications inspired by the advancements of GNNs. Despite this process, there is a notable absence of a systematic review addressing the recent advancement of GNNs in solving mechanics-related tasks. To bridge this gap, this review article aims to provide an in-depth overview of the GNN applications in mechanics-related domains while identifying key challenges and outlining potential future research directions. In this review article, we begin by introducing the fundamental algorithms of GNNs that are widely employed in mechanics-related applications. We provide a concise explanation of their underlying principles to establish a solid understanding that will serve as a basis for exploring the applications of GNNs in mechanics-related domains. The scope of this paper is intended to cover the categorisation of literature into solid mechanics, fluid mechanics, and interdisciplinary mechanics-related domains, providing a comprehensive summary of graph representation methodologies, GNN architectures, and further discussions in their respective subdomains. Additionally, open data and source codes relevant to these applications are summarised for the convenience of future researchers. This article promotes an interdisciplinary integration of GNNs and mechanics and provides a guide for researchers interested in applying GNNs to solve complex mechanics-related tasks.

An Electro-Chemo-Mechanic Model Resolving Delamination between Components in Complex Microstructures of Solid-State Batteries

A novel approach is presented to model delamination and recontacting at internal interfaces of three-dimensional resolved microstructures of solid-state batteries. To resolve the effect of delaminations, we incorporate the consistent enforcement of contact constraints at those interfaces using Nitsche’s method. The model incorporates charge, mass, and momentum conservation to consider electrochemistry, solid mechanics, and their interaction. After introducing and verifying the model, we examine various scenarios to quantify the effect of delaminations at the electrode-solid electrolyte interface on cell performance. The simulations show that increased mechanical stack pressure during cycling mitigates delamination tendencies at the electrode-solid electrolyte interface. Consistent with existing literature, the simulations demonstrate that delaminations increase the internal resistance and reduce the amount of transferred charge. In contrast to experimental analyses, the presented model allows quantitative and in-depth investigations of delamination effects. Furthermore, our analysis of two cell concepts—one assembled in the discharged state and another assembled in the charged state—indicates that half-cells assembled in an initial state from which the active material shrinks in volume upon first charge or discharge show a higher delamination risk at the electrode-solid electrolyte interface. The study highlights the critical relationship between solid mechanics and electrochemistry in consideration of delamination phenomena in solid-state batteries, offering valuable insights for optimizing battery design and performance.

Study on the electromagnetic-thermal-mechanical coupling damage of concrete under microwave irradiation

The paper aims to explore the thermal response of three-dimensional random aggregate concrete model under microwave irradiation. The multi-field distribution in concrete by coupling of the electromagnetics, heat transfer and solid mechanics in COMSOL Multiphysics software under microwave irradiation was investigated. The results shown that the different in dielectric properties and thermal expansion coefficients between aggregate and mortar resulted in the generation of temperature gradients and stress concentration at interface. In addition, due to the larger expansion coefficient of aggregate compared to mortar, stress concentration was formed at interface, promoting the damage of concrete. Microwave power exhibited a notable influence on thermal accumulation and thermal stress. Higher microwave power correlating to higher growth rates of temperature and stress. The Von Mises stress in mortar was significantly greater than that in aggregate, as energy absorption reached a certain threshold, damage occurred in mortar. In addition, microwave frequency significantly influenced the distribution of electric field within the cavity, and also the energy conversion ratio of aggregate within concrete. The study could provide a comprehensive understanding of heating effects of microwave radiation on concrete, providing the mechanical basis for microwave-assisted concrete recovery.

Microstructure evolution by thermomechanical processing and high-temperature mechanical properties of HCP-high entropy alloys (HEAs)

The solid solution strengthening and deformation mechanisms of the hcp-high entropy alloys (HEAs) have not been elucidated yet because of the complexity introduced by the martensite structure, particularly in alloys undergoing phase transformation from bcc to hcp structures. This study attempted to fabricate an equiaxed hcp microstructure for TiZrHf, TiZrHfAl, and TiZrHfAlSc using the hot rolling process and subsequent heat treatment. The equiaxed hcp phase was successfully formed in TiZrHfAl, but the martensite structure remained in TiZrHf and TiZrHfAlSc. The 0.2 % proof stress at 400 and 600°C increased with the increase of the average atomic size misfit δ and the mixing entropy . The low activation volume and high-stress exponent of TiZrHfAl with equiaxed hcp phase at room temperature suggest minor obstacles such as cluster or short-range order inhibit the movement of dislocation and leading to the significant solid-solution strengthening. However, the effect diminished at 600 °C.

An investigation on effect of tramp elements and solidification processing on homogenization kinetics of AA 7xxx series aluminum alloys

AA 7068 Aluminum alloy is produced via conventional solidification (CS) and controlled diffusion solidification (CDS) processing and homogenized at 450 °C for 6 and 12 h. Optical microscopy (OM) and scanning electron microscopy (SEM) equipped with an energy dispersive x-ray spectroscope (EDS) were used to examine the as-cast and homogenized samples. It was found that although the CS sample is more chemically homogenized in the as-solidified state, the CDS sample exhibits a higher homogenization rate during the treatment. The calculated phase diagram (CALPHAD) methodology was employed to study the effect of silicon and iron on the solidification path and homogenization of the alloy. Silicon consumes magnesium atoms on the surface of the α-Al phase to form the Mg2Si phase. Therefore, the magnesium concentration on the α-Al phase required for the formation of the σ phase must be increased. Calculations shows that all the Mg atoms at this stage are completely supplied from the bulk of the αAl phase. It can be hypothesized that during the last stage of solidification, a solid/liquid diffusion couple can be created between the primary αAl and the remaining liquid for several minutes (4 min at a cooling rate of 0.2 oC/s). As a result of the activation of this couple, the Mg atoms diffuse from the α-Al bulk to its surface, and vacancies diffuse from the surface to the bulk, forming a line of Kirkendall voids. With CDS processing, the surface of the primary phase is less Mg-concentrated than that in the CS process and this significantly reduces the formation of the Mg2Si phase. Conversely, the vacancy and Mg concentration of the αAl phase in CDS is higher than that of CS and this lets other alloying elements other than Mg diffuse to the primary phase, decreasing the homogenization time. The presence of Si in the alloy leads to the formation of the Mg2Si phase, which significantly reduces the final Mg concentration in the α-Al phase after full homogenization. In the pure alloy, the Mg concentration is 2.42 wt%, while in the FeSi-containing alloy, it is reduced to 1.58 wt% due to solid solution and dispersion strengthening mechanisms. Through CDS processing, the negative impact of Si can be reduced by disrupting the mechanism of Mg2Si formation.

Shrinkage and deformation of material extrusion 3D printed parts during sintering: numerical simulation and experimental validation

Material extrusion 3D printing (ME3DP) combined with sintering is a low-cost additive manufacturing technique for fabricating components of difficult-to-print metals, such as copper, aluminum, and ceramics. However, the sintering process includes complex material science, such as volumetric shrinkage and free structural bending, to identify the relative density and deformation of a 3D printed sample. The prediction of the relative density and deformations during the sintering process provides information to the design engineer to optimize the design of the CAD model before sintering. In this study, a phenomenological model based on constitutive equations was developed to predict the density and structural deformation during the sintering process of pure copper components fabricated by ME3DP using metal injection molding feedstock. The densification rate was determined using shrinkage estimation with an isothermal stairway heating cycle in a vertical dilatometer. Furthermore, different sets of experiments were performed with a load on the probe with long isothermal heating cycles at 850, 900, 950, 1000, and 1050°C in a vertical dilatometer to estimate the axial viscosity of the copper. The constitutive equations were solved using the solid mechanics module with user-defined creep in COMSOL Multiphysics by considering isotropic assumptions. Two types of geometries, cube and overhanging I section, were used to predict shrinkage and deformation during the sintering process. The developed model successfully predicted the relative density based on shrinkage and structural deformation owing to gravity during the sintering process.

Vitreous Tissue Cryopreservation Using a Blood Vessel Model and Cryomacroscopy for Scale-Up Studies: Observations and Mathematical Modeling

Successful long term cryobanking of multicellular tissues and organs at deep subzero temperatures calls for the avoidance of ice cryoinjury by reliance upon ice-free cryopreservation techniques. However, the quality of the cryopreserved material is the direct result of its ability to survive a host of harmful mechanisms, chief among which is overcoming the trifecta effects of ice crystallization, toxicity, and mechanical stress. This study aims at exploring improved conditions to scale-up ice-free cryopreservation by combining DP6 as a base cryoprotective agent (CPA) solution with an array of synthetic ice modulators (SIMs). This study is conducted by integrating cryomacroscopy techniques, thermal modeling, solid mechanics analysis, and viability and contractility investigation to correlate physical effects, thermal outcomes, and cryobiology results. As an extension of previous work, this study aims at scale-up of established baseline blood vessel models, while comparing the relative toxicity and vitreous stability of 4ml and 10ml samples of DP6 containing either sucrose as a SIM, or the commercial synthetic ice blockers (X1000 and Z1000). Using that established protocol, the addition and removal of DP6+0.6M sucrose and DP6+1%X1000+1%Z1000 were both well tolerated in rabbit carotid and pig femoral artery models, when assessed for metabolic recovery and contractility. Using cryomacroscopy, it was demonstrated that DP6+0.6M sucrose provided a stable vitrification medium under marginal cooling and warming conditions that resulted in >50% survival rate. By contrast, DP6+1%X1000+1%Z1000 was subject to visible ice formation during cooling under the same thermal conditions, resulting in a significantly lower recovery of ∼20%. Thermal modeling is used in this study to verify the actual cooling and rewarming rates in the specimens, while thermo-mechanics analysis is used to explain why fractures were observed using cryomacroscopy when the specimens were contained in glass vials but not in plastic vials.

The hierarchical energy landscape of edge dislocation glide in refractory high-entropy alloys

Refractory high-entropy alloys (RHEAs) are considered as potential candidates for high-temperature applications, with the glide resistance of edge dislocations being a crucial factor in determining the high-temperature strength. However, the solid-solution strengthening mechanism of edge dislocations in RHEAs is not fully understood. The existing Labusch-type models mainly focus on the long-range interaction of solute atoms with the dislocation stress field, while there is little attention paid to the short-range interaction in the dislocation core region. Here, we conduct carefully designed atomic simulations to decouple the long-range and short-range interactions in a typical RHEA, NbMoTaW. Furthermore, the total change in solute-dislocation interaction energy is decomposed, and a hierarchical energy landscape is revealed, demonstrating that the short-range interaction at the core region gains more importance in the solid-solution strengthening of edge dislocations in NbMoTaW. Then, we determine the Larkin length, which signifies the transition from size-dependent to size-independent dislocation behavior. The activation barrier extracted from the simulation with the dislocation length above the Larkin length is incorporated into the crystal plasticity model, and the high-temperature yield strength is well predicted by the strengthening from edge dislocations. Our work provides deep insight into the solid-solution strengthening mechanism in random solution solids, elucidating the importance of the local atomic configuration around the dislocation core.