Experiment Modeling Research Articles

Thermo-hydro-mechanical calibration modelling of the full-scale emplacement experiment and sensitivity analyses

Thermo-hydro-mechanical calibration modelling of the full-scale emplacement experiment and sensitivity analyses

Audiomotor temporal recalibration modulates feeling of control: Exploration through an online experiment and Bayesian modeling.

This online experiment aimed to replicate Sugano's (2021) findings on how exposure to delayed auditory feedback affects feeling of control (agency). Participants first adapted by repeatedly reproducing a sequence of seven, eight or nine tones on a single trial basis while receiving either immediate (10ms) or delayed (110ms) auditory feedback on their keypresses. This exposure aimed to recalibrate their timing perception. Following adaptation, they reproduced the sequence again. However, the computer would assume control of the tone pips starting with the fourth pip from the participants with 50% probability, presenting them at a fixed interval (the average of the first three participant-initiated tones). Participants judged either whether their keypresses caused the tones (agency judgment: AJ) or if the tones felt synchronized with their keypresses (simultaneity judgment: SJ). Analyses revealed similar shifts in both judgments after exposure to delay, however, the AJ exhibited a greater shift compared to the SJ. In addition, the shift reflects a change in bias, not in sensitivity. The result aligns with Sugano's (2021) in-person study, suggesting online experiments can effectively explore agency.

Toward Multi-Dimensional Separation of Nanoparticles in Tubular Centrifuges

The processing and preparation of particulate products is an important process in modern industry and science. The enormous potential for innovation in research and development is due to the complex interactions of solids with their environment. The aim of advanced particle production is to achieve high yields of narrowly distributed particle sizes, shapes or material compositions that provide advantageous product specifications. The integration of solid–liquid separation into these processes expands the process engineering scope in terms of product quality and efficiency. Designing these processes to accommodate a wide range of separation characteristics at small-particle-size scales is a major challenge. Taking these aspects into account, the present work aims to improve a dynamic simulation tool for tubular centrifuges that models the time- and space-dependent mass transport and thus, for the first time, can predict separation outcomes when processing both single- and multi-component systems. Utilizing an optical measurement technique, nanosuspension properties can be measured in real time during separation to support model validation. The simulation results align closely with experimental findings and offer plausible insights when addressing multi-dimensional property distributions of non-spherical particles. This study contributes to advanced modeling of separation experiments in tubular centrifuges in real time, taking into account multiple particle properties such as material density and particle form.

Preferences for breast cancer screening: Results of a discrete choice experiment.

This study aimed to assess the preferences of breast cancer patients in China for screening services using a discrete choice experiment (DCE) and latent class modeling (LCM). The findings are intended to inform the development of more patient-centered screening programs. A cross-sectional, hospital-based survey employing discrete choice experiment methodology. A total of 278 breast cancer patients were recruited from the Department of Thyroid and Breast Surgery at a tertiary hospital in Guizhou Province. The study evaluated key attributes of screening services, including screening frequency, medical staff experience, referral sources, and out-of-pocket costs, through a DCE questionnaire. A mixed logit model was applied to assess overall patient preferences, while LCM was used to explore heterogeneity among patient subgroups. The development of the DCE questionnaire involved focus group discussions to ensure the relevance of attributes. The analysis revealed that screening frequency, medical staff experience, and out-of-pocket costs were the most significant factors influencing patient preferences. Patients exhibited a strong preference for annual screenings (β=-1.622, p<0.001) and for screening by experienced medical staff (β=2.216, p<0.001). Additionally, lower out-of-pocket costs significantly enhanced willingness to participate (β=-0.211, p<0.05). LCM analysis identified two distinct patient subgroups: "process-driven" patients, who prioritized lower costs and multi-channel referral options, and "efficiency-driven" patients, who valued timely service and experienced staff. This study emphasizes the diverse preferences of breast cancer patients for screening services and suggests that personalized screening programs could better meet the needs of different patient subgroups. Developing flexible, patient-centered screening programs will be essential to improving participation and satisfaction with breast cancer screening in China. Practical challenges in implementing such personalized approaches should be considered in future policy development.

Controlling the droplet cell environment in scanning electrochemical cell microscopy (SECCM) via migration and electroosmotic flow.

Scanning electrochemical cell microscopy (SECCM) is a powerful nanoscale electrochemical technique that advances our understanding of heterogeneity at the electrode-electrolyte interface. In SECCM, dual-channel nanopipettes can serve as the probe, and a voltage bias between the channels can control the local electrolyte environment inside the droplet cell via migration and electroosmotic flow (EOF) between the channels, enabling applications including controlled electrodeposition of bimetallic nanoparticles with variable compositions. Herein, we show quantitatively how the voltage bias between the channels modulates the local electrolyte environment via experiment and finite element modeling. Experimentally, redox molecules of different charges (e.g., ferrocene derivatives and Ruthenium(III) hexamine) were filled in separate channels, where their limiting currents at the substrate electrode were used to distinguish the contribution of migration and EOF. Furthermore, EOF was visualized by fluorescence imaging. Finite element models were developed to further validate the experimental results quantitively. We showed that migration is affected by the charge number of the redox molecule. Meanwhile, EOF is affected by the surface charge on the wall of the nanopipette and the location of the slipping plane inside the electrical double layer, which can be tuned by the solution pH and the ionic strength of the electrolyte, respectively. The experimentally validated model can guide the precise modulation of droplet cell environment in SECCM, potentially enabling new scanning modes in SECCM.

Effects of ecological restoration on microbial-mediated ammonia removal in polluted rivers: Microcosm experiment and physical modelling

Effects of ecological restoration on microbial-mediated ammonia removal in polluted rivers: Microcosm experiment and physical modelling

Coupled Hydro-Gas-Mechanical 3D Modeling of LASGIT Experiment

Gas transport simulation in bentonite for radioactive waste disposal poses challenges for numerical models due to its complex microstructure. Understanding the processes involved is a prerequisite for assessing gas flow's impact on repository layouts. The DECOVALEX23 (D-2023) Task B (Large Scale Gas Injection Test: LASGIT) project aims to advance numerical techniques for predicting gas flow in repository systems through gas injection tests on compacted bentonite at the British Geological Survey (BGS). This study develops a comprehensive coupled hydro-gas-mechanical 3D numerical model to simulate the test, considering heterogeneous initial permeability and embedded fractures. Addressing bentonite swelling, three gap closure scenarios for the canister-bentonite blocks gap interface were considered. The model reproduces observed test behaviors, capturing preferential gas flow paths. Sensitivity analysis explores variations in volume factor sensitivity, calibration, hydraulic conductivity of interfaces, heterogeneity, permeability, and model parameters, contributing to a deeper understanding of the phenomenon's complexity. The proposed hydraulic modeling, enriched by considerations of gap closure states, predicts measured evolution of gas injection trends. suggesting reliability and potential applicability for similar conditions and facilitating a comprehensive analysis of its impact on gas testing processes. Additionally, the embedded fracture models underscore the critical role of fracture behavior and dilatancy in determining the system's hydro-mechanical response, with significant sensitivity to these factors influencing stress and pore pressure evolution. Hydro-mechanical models demonstrate that modeling approaches involving embedded fractures and dilatancy significantly influence gas pathways and entry gas pressure. System volume plays pivotal role in the analysis, while sensitivity analysis of contact transmissivity reveals potential influences on preferential gas pathway formation. Hydraulic and hydro-mechanical modeling methods show promise for further numerical investigations, indicating potential for yielding meaningful insights in future studies.

In-situ experiment and numerical modelling of the intragranular and intergranular damage and fracture in plastic deformation of ductile alloys

In-situ experiment and numerical modelling of the intragranular and intergranular damage and fracture in plastic deformation of ductile alloys

Enhanced cyclic stability of NiTi shape memory alloy elastocaloric materials with Ni4Ti3 nanoprecipitates: Experiment and phase field modeling

Enhanced cyclic stability of NiTi shape memory alloy elastocaloric materials with Ni4Ti3 nanoprecipitates: Experiment and phase field modeling

Algebraic Modelling of Experiments on the Example of Proton Therapy

Introduction. Despite the rapid development of the chemical industry and science, discoveries in the field of health care, the emergence of drugs and therapeutics based on nanotechnology and the development of radiation therapy technologies, the safety of biomedical applications of the latest products, and the search for new methods and approaches to the diagnosis and treatment of cancer are an open issue. One of the safest and fastest methods for researching the behaviour of new materials and tools and selecting the best candidates is the modelling of relevant processes, particularly computer molecular modelling based on mathematical models. However, despite a large number of available methods and modelling tools, for most of them, the successful application is possible only for a narrow range of tasks and experiments. As one of the possible solutions to this problem, we propose a new approach to computer molecular modelling based on the synergy of the algebraic approach, namely, algebraic modelling and biological knowledge at different levels of abstraction, starting from quantum interactions to interactions of biological systems. We see one of the directions of application of this approach in the possibilities of modelling the radiation therapy process – starting from modelling the accelerators’ work and ending with modelling the interaction of the particles’ beam with the matter at the level of quantum interactions. In particular, in the article, we consider the possibilities of forward (specific and symbolic) and backward (symbolic) algebraic modelling on the example of models of the higher level of abstraction, which allows us to visualize certain interactions and to build charts of dependencies for specific models, and to determine the presence of the desired scenarios (forward modelling) or a set of initial environment parameters (backward modelling) in symbolic form.

Experiment Modelling of Automated Verification Control on Environmental Conditions During Crop Storage

The study introduces a preliminary approach to enhance the supervision of food processing operators. Specifically, it showcases a digital model of an online compliance validation system with environmental conditions designed for food processing and preservation items that are sensitive to climate factors. The technology demonstration involves four fundamental stages carried out in a complete experimental cycle, where intelligent sensors gather and transmit data through a low-power wireless wide-area network from a farm specializing in sunflower seed storage. Subsequently, six consecutive scripts are executed, five of which are coded in Python. The integration of distributed data technology brings objectivity to the process of securely storing environmental parameters and objectively verifying their compliance with recommended hygienic, bio certification standards. As a result, monitoring the food production process becomes more publicly accessible and with higher rates of objectivity in decisions, enabling prospective buyers and certification agencies to assess the quality of food products with great precision. Therefore, the suggested digital model has the potential to ensure the utmost transparency in the food processing sector.

Next Generation Solid-State Batteries for Electric Aviation

Energy storage will play a critical role in the success of future NASA missions that require batteries with higher energy density, higher power, and most critically improved safety. These performance requirements, which extend beyond those for electric automobile markets, must be satisfied to enable widespread adoption of electric aviation. One approach to improve battery safety and energy is to transition to non-volatile solid-state electrolytes (SSE) which promise many advantages over traditional flammable liquid electrolytes and may also be an enabling technology for next generation chemistries such as lithium-sulfur (Li-S). However, significant manufacturing challenges must be overcome before the adoption of such technology. This study will discuss development of solid electrolytes specifically designed to meet future NASA electric aviation targets. Separator films were processed with densified thickness between 20-30 microns using solvent processing techniques [1]. These films were produced 10-15 times thinner than comparable bulk pressed powder electrolytes and achieved thicknesses comparable to commercial polyolefin separators (25 micron) used in commercial liquid containing lithium-ion cells. Furthermore, design considerations and fabrication techniques of novel cathode composites optimized through the integration of experiment and particle dynamics modeling will be discussed [2] [3]. [1] Donald A. Dornbusch, Rocco P. Viggiano, John W. Connell, Yi Lin, Vadim F. Lvovich. Practical considerations in designing solid state Li-S cells for electric aviation, Electrochimica Acta, 2021, 139406, ISSN 0013-4686,[2] Vesselin I. Yamakov, April A. Rains, Jin Ho Kang, Lopamudra Das, Rehan Rashid, Ji Su, Rocco P. Viggiano, John W. Connell, Yi Lin. Pressure Dependence of Solid Electrolyte Ionic Conductivity: A Particle Dynamics Study. ACS Applied Materials & Interfaces 2023, 15 (22) , 27243-27252.[3] Elizabeth A. Barrios, April A. Rains, Yi Lin, Ji Su, John W. Connell, Rocco P. Viggiano, Donald A. Dornbusch, James J. Wu, and Vesselin Yamakov. Li-Ion Permeability of Holey Graphene in Solid State Batteries: A Particle Dynamics Study. ACS Appl. Mater. Interfaces 2022, 14, 18, 21363–21370.

Uncertainty quantification of material parameters in modeling coupled metal and high explosive experiments

Experiments involving the coupling of metal and high explosives (HE) are of notable defense-related interest, and we seek to refine the uncertainty quantification associated with models of such experiments. In particular, our focus is on how uncertainty related to the metal constitutive model challenges our ability to infer high explosive model parameters when analyzing focused science experiments. We consider three focused experiments involving an HE accelerating metal: small plate tests with tantalum/LX-14 and tantalum/LX-17 pairings as well as a tantalum/LX-17 cylinder test. For all three models, we perform sensitivity analysis to ascertain the influence of metal strength on the coupled experimental response. Moreover, we calibrate each model in a Bayesian setting and study the quantification of metal strength on the inference of the HE parameters. Based on our results, we offer guidance for future metal/HE experiments.

In-situ impedance diagnosis experiment and equivalent circuit modeling based on distribution of relaxation time method for unitized regenerative proton exchange membrane fuel cells

The Distribution of Relaxation Times (DRT) method provides a powerful approach for analyzing Electrochemical Impedance Spectroscopy (EIS) in electronic components, enabling clear separation of different impedance types and accurate equivalent circuit modeling. In this study, the DRT method was applied to unitized regenerative proton exchange membrane fuel cells (UR-PEMFCs) for the first time, establishing an impedance quantification model for in-situ diagnostics of multiple impedances. This foundational framework supports future durability testing efforts. In-situ impedance diagnostics were conducted in both Fuel Cell (FC) and Electrolytic Cell (EC) modes using a custom mode-switching platform. Results show that under constant electrode conditions, the bifunctional membrane electrode enhances round-trip efficiency by 15.75% compared to the constant gas mode. Through DRT imaging in FC and EC modes, impedance information corresponding to distinct relaxation peaks was extracted and assigned based on operational experiments. The three main peaks identified in both modes were attributed to proton transfer impedance, charge transfer impedance, and mass transfer impedance. Additionally, variations in operating conditions led to the appearance of new transport mechanisms within the charge transfer impedance. In FC mode, the DRT-based equivalent circuit model achieved precise fitting. Applying DRT to UR-PEMFCs improves water and bubble management, offering efficient optimization pathways and valuable guidance for cell design, operational parameter refinement, and durability monitoring.

Topological and site disorder in boron nitride networks.

Amorphous boron nitride (a-BN) is modelled over a wide range of densities using a relatively simple potential model augmented with site charges. The local topology (defined, for example, through the total nearest-neighbour coordination number), appears near-constant across a wide range of densities and site charges. Furthermore,totalscattering andtotalpair distribution functions also show few changes as a function of either density or site charge. Variation of the site charges directly controls the level of site (rather than topological) disorder meaning that although total pair functions may be near-constant, the underlying partial contributions may be very different. Direct contact is made with both experiment and (more recent) density-functional theory-based modelling work.

Hybrid CFRP‐GFRP sheets for flexural strengthening of continuous RC beams: Experimentation and analytical modeling

AbstractContinuous reinforced concrete (RC) beams cast in place are commonly used in construction; however, there is a notable gap in the literature regarding the performance of continuous RC beams strengthened with fiber‐reinforced polymer (FRP) sheets. Strengthening RC beams with FRP sheets typically leads to reduced ductility and moment redistribution capacity due to the linear stress–strain behavior of FRP materials compared to non‐strengthened RC beams. Addressing this gap, this study explores the feasibility of enhancing the mechanical properties and ductility of strengthened elements through a hybrid approach, combining carbon‐fiber‐reinforced polymer (CFRP) and glass‐fiber‐reinforced polymer (GFRP) sheets. An experimental program was conducted, retrofitting two continuous two‐span RC beams (250 × 150 × 6000 mm) with hybrid CFRP‐GFRP (HCG) sheets. Concentrated loads were applied at the center of each span, and comprehensive data on strains in FRP sheets, longitudinal reinforcements, and crack propagation patterns were recorded and meticulously analyzed. The outcomes demonstrated that employing HCG sheets for strengthening RC continuous beams significantly improves ductility, load‐carrying capacity, and moment redistribution, surpassing the performance of beams strengthened with either CFRP or GFRP sheets. To ensure accurate predictions of the flexural response, an analytical model was developed and rigorously verified using the experimental results. The model takes into account the strain compatibility condition and provides insights into the behavior of continuous RC beams strengthened with CFRP, GFRP, and HCG sheets. This research contributes valuable knowledge to the understanding of FRP sheet strengthening techniques, emphasizing the efficacy of HCG sheets for achieving enhanced structural performance in continuous RC beams.

Exploring Wire-Arc Additive Manufactured Rivets for Joining Hybrid Electrical Busbars

This paper presents a joining by plastic deformation process for fabricating hybrid electrical busbars made from copper and aluminum sheets. The process comprises the innovative use of wire-arc additive manufacturing to deposit copper rivets at specific locations on the copper sheets, the machining of slots with the required geometry in the aluminum sheets, and the compression of the copper sheets to force the rivets into the pre-machined slots of the aluminum sheets, creating form-closed mechanical interlocks. The work combines experimentation and finite element modeling to analyze the influence of the most significant process parameters, and the electrical performance of the hybrid busbar joints is evaluated and compared to that of conventional fastened joints at different service temperatures. Results demonstrate the effectiveness and potential advantages of the new joining by plastic deformation process for fabricating hybrid electrical busbars.

Unravelling Coupled Hydrological and Geochemical Controls on Long-Term Nitrogen Enrichment in a Large River Basin.

Many groundwater and surface water bodies around the world show a puzzling and often steady increase in nitrogen (N) concentrations, despite a significant decline of agricultural N inputs. This study uses a combination of long-term hydrogeochemical and hydraulic monitoring, molecular characterization of dissolved organic matter (DOM), column experiment, and reactive transport modeling to unravel the processes controlling N-reactive transport and mass budgets under the impacts of dynamic hydrologic conditions at a field site in the central Yangtze River Basin. Our analysis shows that the desorption of ammonium (NH4+) from sediments via cation exchange reactions dominates N mobilization and aqueous N concentrations, while the mineralization of organic N compounds plays only a minor role. The reactive transport modeling results illustrate the important role of cation exchange reactions that are induced by temporary NH4+ input and cation concentration changes under the impact of both seasonal and long-term hydrologic variations. Historically, cation exchangers have acted as efficient storage devices and mitigated the impacts of high levels of NH4+ input. The NH4+ residing on cation exchanger sites later acts as a long-term N source to waters with the delayed desorption of sediment-bound NH4+ induced by the change of hydrologic conditions. Our results highlight the complex linkages between highly variable hydrologic conditions and NH4+ partitioning in near-surface, river-derived sediments.

How Wetting and Drainage Cycles and Wetting Angle Affect Capillary Air Trapping and Hydraulic Conductivity: A Pore Network Modeling of Experiments on Sand

Entrapped air in porous media can significantly affect water flow but simulations of air entrapment are still challenging. We developed a pore-network model using quasi-static algorithms to simulate air entrapment during spontaneous wetting and subsequent drainage processes. The model, implemented in OpenPNM, was tailored to replicate an experiment conducted on a medium-sized unconsolidated sand sample. We started building the model with three types of relatively small networks formed by 54,000 pore bodies which we used to calibrate basic network topological parameters by fitting the model to the water retention curve and the saturated hydraulic conductivity of the sand sample. Using these parameters, along with X-ray image data (µCT), a larger network formed by over 250,000 pore bodies was introduced in the form of stacked sub-networks where topological parameters were scaled along the z-axis. We investigated the impact of two different contact angles on air entrapment. For a contact angle of 0, the model showed good agreement with the experimental data, accurately predicting the amount of entrapped air and the saturated hydraulic conductivity. On the contrary, for a contact angle of π/4, the model provided reasonable accuracy for saturated hydraulic conductivity but overestimated the amount of entrapped air. Overall, this approach demonstrated that a reasonable match between simulated and experimental data can be achieved with minimal computational costs.

Investigating formability of AZ31B magnesium alloy sheet with different texture and thickness in combination of the Erichsen experiment and CPFEM model

In this study, the formability of the AZ31B magnesium alloy sheets was investigated in combination of experiment and CPFEM modelling. The deformation mechanisms during the Erichsen forming were revealed and the effect of the related parameters were discussed. It was shown that the simulation results based on the normalized Cockcroft-Latham criterion are consistent with the experimental results. The maximum stress and strain concentrate at the center of dome, and exhibit an elliptical distribution shape. The difference of asymmetry situation between the sheets results from the different textures. The basal <a> slip is the dominant mode, and the prismatic <a> slip is also active to accommodate plastic strain in sheet plane. The relative activity of the pyramidal <c+a> slip is low, but very effective to accommodate the plastic strain in thickness direction. The sheet with higher relative activity of the prismatic <a> and pyramidal <c+a> slips exhibit higher formability. The sheet thickness influences the formability through changing the stress-strain response, as well as the orientation-relationship between stress state and grains which can affect the deformation mechanisms. The formability depends on the plastic strain accommodation ability that is comprehensively related to the averaged plasticity, orientation-relationship between stress state and grains, r-value and n-value. CPFEM modeling is convenient pathway to predict the formability.