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At least 307 records · Page 17

A New Martian Crater Chronology: Implications for Jezero Crater

Crater chronologies are a fundamental tool to assess the relative and absolute ages of planetary surfaces when direct radiometric dating is not available. Martian crater chronologies are derived from lunar crater spatial densities on terrains with known radiometric ages, and thus they critically depend on the Moon-to-Mars extrapolation. This extrapolation requires knowledge of the time evolution of the impact flux, including contributions from various impactor populations, factors that are not trivially connected to the dynamical evolution of the early Solar System. In this paper, we will present a new Martian crater chronology based on current dynamical models, and consider the main sources of uncertainties (e.g., impactor size–frequency distribution; dynamical models with late and early instabilities, etc.). The resulting “envelope” of Martian crater chronologies significantly differs from previous chronologies. The new Martian crater chronology is discussed using two interesting applications: Jezero crater’s dark terrain (relevant to the NASA Mars 2020 mission) and the southern heavily cratered highlands. Our results indicate that Jezero’s dark terrain may have formed ∼3.1 Ga, i.e., up to 0.5 Gyr older than previously thought. In addition, available crater chronologies (including our own) overestimate the number of craters larger than 150 km on the southern highlands, suggesting either that large craters have been efficiently erased over Martian history or that dynamical models need further refinement. Further, our chronology constrains the age of Isidis basin to be 4.05–4.2 Ga and that of the Borealis basin to be 4.35–4.40 Ga; these are predictions that can be tested with future sample and return missions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Recovering the phase and amplitude of X-ray FEL pulses using neural networks and differentiable models

Dynamics experiments are an important use-case for X-ray free-electron lasers (XFELs), but time-domain measurements of the X-ray pulses themselves remain a challenge. Shot-by-shot X-ray diagnostics could enable a new class of simpler and potentially higher-resolution pump-probe experiments. Here, we report training neural networks to combine low-resolution measurements in both the time and frequency domains to recover X-ray pulses at high-resolution. Critically, we also recover the phase, opening the door to coherent-control experiments with XFELs. The model-based generative neural-network architecture can be trained directly on unlabeled experimental data and is fast enough for real-time analysis on the new generation of MHz XFELs.

42 ENGINEERING↗

System risk quantification and decision making support using functional modeling and dynamic Bayesian network

Risk-informed decision-making requires a probabilistic assessment of the likelihood of success of control action, given the system status. This paper presents a systematic state transition modeling approach integrating dynamic probabilistic risk assessment with a decision-making process using a dynamic Bayesian network (DBN) coupled with functional modeling. A functional model designed with multilevel flow modeling (MFM) technique was used to build a system state structure inferred by energy, mass, and information flow so that one can verify the developed model with respect to system functionality. The MFM model represents the causal relationship among the nodes, which captures the structure of process parameters and control units. Each node may have multiple possible states, and the DBN structured by the MFM model represents the time-domain transitions among the defined states. Furthermore, the MFM-DBN integrated state transition modeling is a white-box approach that allows one to draw the system's risk profile by updating the system states and supports the decisions probabilistically with physical inference. An example of a simple heating system has been used to illustrate this process, including decision-making support based on quantitative risk profile. For demonstrating its applicability to a complex system operational decision making, a case study of station blackout accident scenario leading to the seal loss of coolant accident in a nuclear power plant is presented. The proposed approach effectively provided the risk profile along time for each option so that the operators can make the best decision, which minimizes the plant risk.

42 ENGINEERING↗

Phase field dislocation dynamics (PFDD) modeling of non-Schmid behavior in BCC metals informed by atomistic simulations

Body-Centered Cubic (BCC) metals exhibit anomalous mechanical properties such as twinning/anti-twinning and tension/compression asymmetry, which are attributed to asymmetric behavior of screw dislocations. Unlike Face-Centered Cubic (FCC) metals, the Critical Resolved Shear Stress (CRSS) of BCC metals deviates from the Schmid law. Here, we use a mesoscale modeling approach called Phase Field Dislocation Dynamics (PFDD) to understand the critical factors that control this non-Schmid behavior and reproduce atomistic predictions of the CRSS (Peierls stress). All inputs to the PFDD model are obtained from Molecular Statics (MS) simulations. Multiple pathways for modeling the non-Schmid behavior are investigated by incorporating the representative dislocation properties into different energy terms in the PFDD model. One way to understand non-Schmid behavior is to incorporate stress components projected on inclined planes into the external energy term within PFDD. Alternatively, we propose that non-Schmid behavior can also be accounted for by considering the variation of the {110} unstable stacking fault energy and the dislocation core width as a function of the applied tensorial stress field. The CRSS predicted using PFDD modeling is in excellent agreement with MS predictions.

36 MATERIALS SCIENCE↗

A Model-Free Voltage Control Approach to Mitigate Motor Stalling and FIDVR for Smart Grids

Electric power networks are large and highly nonlinear dynamical systems that present unique challenges to control design. Though there is a large number of dynamic models for power system stability and control, many models are only useful with right assumptions and wrong for other tasks. Moreover, the dynamic behavior of the grid is increasingly complex under the banner of smart grids. These lead to the difficulty of developing appropriate dynamic modeling, and thus an efficient control strategy. To avoid such modeling challenges, here we present a novel dynamic voltage control strategy based on a model-free control (MFC) approach, requiring no modeling procedure. In particular, it focuses on fault-induced delayed voltage recovery (FIDVR) events, which require complex and accurate dynamic load models to replicate such events. This work utilizes MFC as an online controller to achieve the desired voltage stability under the FIDVR event. The proposed MFC strategy allows simple implementation and low computational cost for efficient mitigation of FIDVR. For benchmarking, a reasonably accurate dynamic performance model is explored. Simulation results with the IEEE 57 bus test network demonstrate the enhanced dynamic voltage profile for load buses having induction motors with the support of reactive power resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Autoregressive distributed lag-based dynamic uniformity modeling and monitoring approaches for superconductor manufacturing

High-temperature superconductors (HTS), known for their high efficiency and low energy loss, have found profound applications across various fields, driving the demand for long, uniformly performing tapes. However, ensuring uniform performance over extended lengths of HTS tapes, often characterized by the consistency of critical current, remains challenging due to fluctuations in growth conditions during manufacturing. Here, to elucidate the mechanisms underlying variations in tape uniformity and enable real-time monitoring of associated parameters, we propose an Autoregressive Distributed Lag (ADL)-based Dynamic Uniformity Modeling and Monitoring (ADUM2) approach. This method integrates uniformity measurement, the identification of critical process parameters and real-time monitoring within the manufacturing process. The ADUM2 approach is applied to the advanced metal organic chemical vapor deposition (A-MOCVD) process, a pilot-scale method for superconductor manufacturing. Our model demonstrates superior performance compared to benchmark methods, accounting for over 80% of the total variance in the data and identifying 13 key process parameters influencing the uniformity of HTS tapes. This study offers significant insights into the high-temperature superconductor manufacturing process and holds the potential to facilitate the production of cost-effective, uniformly performing long superconducting tapes in the future.

autoregressive distributed lag analysis↗

Modelling of parallel dynamics of a pellet-produced plasmoid

The parallel expansion of a dense, pellet-produced plasmoid is modelled with parameters relevant to pellet fuelling experiments in the Wendelstein7-X stellarator. Good agreement is found between the analytical theory and more detailed modelling. In particular, much of the energy deposited in the pellet by the ambient plasma is transferred to the pellet ions by the ambipolar electric field during the expansion. The validity of the hydrodynamic treatment of the plasmoid and the ambient plasma is discussed.

Physics↗

Model-Free Dynamic Voltage Control of a Synchronous Generator-Based Microgrid

The main goal of this paper is to present a new dynamic voltage stability mechanism, based on model-free control (MFC), for effective control and coordination of synchronous generator (SG)-based reactive power resources in a microgrid setting. MFC has shown successful operation in various domains, and this paper presents its first use in the voltage stability of a power system. It is utilized as an online controller to achieve the dynamic voltage stability of a microgrid system under different disturbances and fault conditions. A 21-bus microgrid system fed by SG-based distributed energy resources (DERs) is considered as a use case study. The overall dynamic voltage stability of the microgrid system is investigated using time-domain dynamic simulations during emergency, hazard, and disaster events. Simulation results show that there are significant improvements and enhancements on the dynamic load bus voltage profiles of the microgrid system by the effective model-free control and coordination of the reactive power reserves of the SG-based DERs.

Hatipoglu, Kenan↗

Modeling the dynamic response of rock masses with multiple compliant fluid saturated joint sets - Part II: Continuum modeling

Part I of this two-part paper describes enhancements of a mesoscale model to include: many non-persistent fluid saturated joints with finite area, normal compliance with hysteresis and the weakening effects of angular deviation in the joint sets and of fluid pressure in the joints. The objective of this Part II is to use the results of the mesoscale model as simulated data to inspire functional forms in a continuum model for rock masses with multiple compliant fluid saturated joint sets which include these enhancements. Also, an algorithm is proposed for reducing the number of joint sets being modeled. Examples are presented here which show that the continuum model can predict similar anisotropic response to that observed in mesoscale simulations. In contrast with the mesoscale model, the continuum model can be used for large scale simulations of real applications, smoothly transitioning from coupled inelastic thermomechanical response near an explosive source to orthotropic elastic response far from the source.

58 GEOSCIENCES↗

A Dynamic Pore Network Model for Imbibition Simulation Considering Corner Film Flow

Wetting films can develop in the corners of angular pores under strong wetting conditions. Modeling the dynamics of corner film remains elusive using direct numerical simulations because of the significant scale difference between main meniscus and corner film flow. In this paper, the modified interacting capillary bundle model (ICB), developed in our previous work to describe accurately corner film dynamics in a single square tube, is incorporated into a single-pressure dynamic pore network model (DPNM) to simulate imbibition in strongly wetting porous media with corner film flow. The traditional pore network is decomposed into several layers of interacting subpore networks where the 0th layer of subpore network simulates the main meniscus flow and higher layers the corner film flow. The fluid flow between different layers is captured by interlayer throats. In addition, the snap-off mechanism caused by the thickening of wetting corner film is considered. The accuracy of the developed model is validated for four cases: spontaneous imbibition in a single square tube, wetting fluid redistribution through corner films under a capillary pressure difference, snap off in a narrow throat connecting two large pores, and imbibition dynamics in a real microfluidic porous geometry. The validated model is then used to simulate both spontaneous and controlled imbibition in a pore network with random pore size distribution. Finally, the interaction between corner film and main meniscus flow in porous media is analyzed from a pore-scale perspective.

58 GEOSCIENCES↗

A dynamic price model based on supply and demand with application to techno-economic assessments of rare earth element recovery technologies

Rare Earth Elements (REEs) are essential for sustainable energy technologies. Techno-economic Assessments (TEAs) have been conducted to evaluate innovative approaches to recover REEs from waste streams. However, most TEA studies do not consider the price volatility of REEs, which raises concern over the reliability of the analysis in an unpredictable dynamic market. To address this shortcoming, a dynamic price model is proposed that adjusts REE price based upon supply-demand conditions. The dynamic market behavior is simulated and its effect on a TEA is examined via a case study. The results of the dynamic simulation indicate a growing trend of the market price for REE materials/products. Compared to a conventional TEA that does not consider price dynamics, a significant difference in economic performance metrics is identified from the dynamic TEA results. Finally, the proposed dynamic TEA method is not limited to a specific application and can provide insights for evaluating a broad range of technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Observation and Modeling of Dynamic Fracture Behaviors of Battery Cell Under Impact Loading Using Enhanced Representative Volume Element Concept

The burgeoning electric automobile industry has increased interest in battery safety. Battery cells experience significant mechanical stress during operation, including the impact of accidents and vibrations from driving. The potential for thermal runaway reactions in battery cells raises safety concerns. Although numerous researchers have defined the dynamic behavior of battery cells and proposed numerical models to describe it, few studies have focused on the high-strain rate mechanical impact phase correlated with the onset of fracture. In this study, we describe the dynamic behavior of pouch battery cells and propose a modeling method to study their mechanical failure under impact situations. Impact tests are conducted at various velocities and heights. To overcome numerical issues commonly encountered under rapid deformation scenarios, a new finite element model is developed based on the representative volume element model. The proposed approach efficiently simulates continuous crack propagation and brittleness behavior during impact by permitting the individual behavior of the cell components. Therefore, engineers can reliably design safer electric vehicle battery cells by measuring the properties of the cell components.

ENERGY STORAGE↗

Dynamic condensation model of rolling droplets for high-performance heat transfer

Condensation is a critical process during vapor-liquid phase change in relation to heat transfer. To achieve a high heat transfer coefficient, the classical model for dropwise condensation requires a low contact angle and low contact angle hysteresis, failing to align with experimental observations on a hydrophobic and slippery quasi-liquid surface (QLS). Here, we report a dynamic condensation model that incorporates high-frequency condensate removal by emphasizing the role of timescale during droplet growth and shedding. Our model agrees well with the experimental result that a surface with high contact angle and low contact angle hysteresis promotes condensation, particularly during rolling-propelled condensate removal. Particle image velocimetry reveals that rolling droplets on a hydrophobic QLS exhibit 4-fold higher shedding speeds than the sliding droplets on a hydrophilic QLS, leading to significant heat transfer enhancement. This work deepens our theoretical understanding of condensation heat transfer and provides advanced physics-informed design rationales for water and energy systems.

42 ENGINEERING↗

MECHANICAL SHOCK AND VIBRATION ANALYSIS OF SPENT NUCLEAR FUEL CARRIED BY THE ATLAS RAILCAR

Researchers at Pacific Northwest National Laboratory have completed a structural-dynamic analysis of spent nuclear fuel subjected to the mechanical shock and vibration environment that is anticipated during normal conditions of transport in casks carried by the Atlas railcar. The Atlas railcar is a new railcar design that is being developed specifically for the purpose of carrying spent nuclear fuel casks. The analysis used best-estimate railcar dynamics models of the Atlas railcar and considered 17 different spent nuclear fuel transportation cask systems, representing the current fleet of cask options. This work used NUCARS, a specialized railcar dynamics explicit finite element code to calculate railcar dynamic response to prescribed speeds and track configurations. The railcar dynamics models provided cask transient motion for a wide range of speeds and track conditions, generating a relatively large database of potential cask motion. All of the cask motion transients were then applied as loading conditions to LS-DYNA structural-dynamic models of a single fuel rod. The analyses predict that the Equipos Nucleares S.A./U.S. Department of Energy (ENSA/DOE) multimodal transportation test of 2017 provided a relatively stronger vibration environment than is expected from the Atlas railcar. This paper describes the analysis methods, the analysis results, and compares the results of the Atlas transportation analysis to the test results and analyses of the ENSA/DOE multimodal transportation test of 2017.

Klymyshyn, Nicholas A.↗

Reformulating a Gurson-based dynamic damage model and demonstrating improved predictive power and numerical robustness

The original Tepla (TEnsile PLAsticity) ductile damage model, based on the Gurson yield surface, has long been used to model damage evolution and material failure under dynamic loading. Unfortunately, Tepla suffered from mesh sensitivity, numerical instability, and limited predictive capability. Here, we theoretically reformulate Tepla to address these issues. We especially focus on the prediction of porosity, which is the key state variable used for modeling ductile damage, as compared to more easily measured surface velocities, which are at best an indirect measure of damage. Key model changes include separating the viscosity during volumetric void growth from underlying shear strength behavior and switching to an iterative bisection solver. The new Tepla is then calibrated on incipient spall experiments on half-hard copper and tantalum, which demonstrate its ability to simultaneously fit the model to recovered porosity distributions and measured surface velocities, a stringent test. Improved numerical behavior, such as greatly reduced mesh sensitivity, is also shown in those simulations. Finally, the new Tepla model is applied to several high-explosive loaded, sweeping wave experiments, showing the ability of the model to predict behavior on tests with significantly different loading conditions and histories than the calibration data.

36 MATERIALS SCIENCE↗

A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure

In this work, cascading transmission line failures are studied through a dynamical model of the power system operating under fixed conditions. The power grid is modeled as a stochastic dynamical system where first-principles electromechanical dynamics are excited by small Gaussian disturbances in demand and generation around a specified operating point. In this context, a single line failure is interpreted in a large deviation context as a first escape event across a surface in phase space defined by line security constraints. The resulting system of stochastic differential equations admits a transverse decomposition of the drift, which leads to considerable simplification in evaluating the quasipotential (rate function) and, consequently, computation of exit rates. Tractable expressions for the rate of transmission line failure in a restricted network are derived from large deviation theory arguments and validated against numerical simulations. Extensions to realistic settings are considered, and individual line failure models are aggregated into a Markov model of cascading failure inspired by chemical kinetics. Cascades are generated by traversing a graph composed of weighted edges representing transitions to degraded network topologies. Numerical results indicate that the Markov model can produce cascades with qualitative power-law properties similar to those observed in empirical cascades.

Kinetic Monte Carlo, rare events, Cascading Failur↗

Physics and technology considerations for the deuterium–tritium fuel cycle and conditions for tritium fuel self sufficiency

The tritium aspects of the DT fuel cycle embody some of the most challenging feasibility and attractiveness issues in the development of fusion systems. The review and analyses in this paper provide important information to understand and quantify these challenges and to define the phase space of plasma physics and fusion technology parameters and features that must guide a serious R&D in the world fusion program. We focus in particular on components, issues and R&D necessary to satisfy three 'principal requirements': (1) achieving tritium self-sufficiency within the fusion system, (2) providing a tritium inventory for the initial start-up of a fusion facility, and (3) managing the safety and biological hazards of tritium. A primary conclusion is that the physics and technology state-of-the-art will not enable DEMO and future power plants to satisfy these principal requirements. We quantify goals and define specific areas and ideas for physics and technology R&D to meet these requirements. A powerful fuel cycle dynamics model was developed to calculate time-dependent tritium inventories and flow rates in all parts and components of the fuel cycle for different ranges of parameters and physics and technology conditions. Dynamics modeling analyses show that the key parameters affecting tritium inventories, tritium start-up inventory, and tritium self-sufficiency are the tritium burn fraction in the plasma (f b ), fueling efficiency (η f ), processing time of plasma exhaust in the inner fuel cycle (t p ), reactor availability factor (AF), reserve time (tr) which determines the reserve tritium inventory needed in the storage system in order to keep the plant operational for time t r in case of any malfunction of any part of the tritium processing system, and the doubling time (t d ). Results show that η f f b > 2% and processing time of 1–4 h are required to achieve tritium self-sufficiency with reasonable confidence. For η f f b = 2% and processing time of 4 h, the tritium start-up inventory required for a 3 GW fusion reactor is ~11 kg, while it is <5 kg if η f f b = 5% and the processing time is 1 h. To achieve these stringent requirements, a serious R&D program in physics and technology is necessary. The EU-DEMO direct internal recycling concept that carries fuel directly from the plasma exhaust gas to the fueling systems without going through the isotope separation system reduces the overall processing time and tritium inventories and has positive effects on the required tritium breeding ratio (TBR R ). A significant finding is the strong dependence of tritium self-sufficiency on the reactor availability factor. Simulations show that tritium self-sufficiency is: impossible if AF < 10% for any η f f b , possible if AF > 30% and 1% ≤ η f f b ≤ 2%, and achievable with reasonable confidence if AF > 50% and η f f b > 2%. These results are of particular concern in light of the low availability factor predicted for the near-term plasma-based experimental facilities (e.g. FNSF, VNS, CTF), and can have repercussions on tritium economy in DEMO reactors as well, unless significant advancements in RAMI are made. There is a linear dependency between the tritium start-up inventory and the fusion power. The required tritium start-up inventory for a fusion facility of 100 MW fusion power is as small as 1 kg. Since fusion power plants will have large powers for better economics, it is important to maintain a 'reserve' tritium inventory in the tritium storage system to continue to fuel the plasma and avoid plant shutdown in case of malfunctions of some parts of the tritium processing lines. But our results show that a reserve time as short as 24 h leads to unacceptable reserve and start-up inventory requirements. Therefore, high reliability and fast maintainability of all components in the fuel cycle are necessary in order to avoid the need for storing reserve tritium inventory sufficient for continued fusion facility operation for more than a few hours. The physics aspects of plasma fueling, tritium burn fraction, and particle and power exhaust are highly interrelated and complex, and predictions for DEMO and power reactors are highly uncertain because of lack of experiments with burning plasma. Fueling by pellet injection on the high field side of tokamak has evolved to be the preferred method to fuel a burning plasma. Extrapolation from the DIII-D penetration scaling shows fueling efficiency expected in DEMO to be <25%, but such extrapolations are highly uncertain. The fueling efficiency of gas in a reactor relevant regime is expected to be extremely poor and not very useful for getting tritium into the core plasma efficiently. Gas fueling will nonetheless be useful for feedback control of the divertor operating parameters. Extensive modeling has been carried out to predict burn fraction, fueling requirements, and fueling efficiency for ITER, DEMO, and beyond. The fueling rate required to operate Q = 10 ITER plasmas in order to provide the required core fueling, helium exhaust and radiative divertor plasma conditions for acceptable divertor power loads was calculated. If this fueling is performed with a 50–50 DT mix, the tritium burn fraction in ITER would be ~0.36%, which is too low to satisfy the self-sufficiency conditions derived from the dynamics modeling for fusion reactors. Extrapolation to DEMO using this approach would also yield similarly low burn fraction. Extensive analysis presented shows that specific features of edge neutral dynamics in ITER and fusion reactors, which are different from present experiments, open possibilities for optimization of tritium fueling and thus to improve the burn fraction. Using only tritium in pellet fueling of the plasma core, and only deuterium for edge density, divertor power load and ELM control results in significant increase of the burn fraction to 1.8–3.6%. These estimates are performed with physics models whose results cannot be fully validated for ITER and DEMO plasma conditions since these cannot be achieved in present tokamak experiments. Thus, several uncertainties remain regarding particle transport and scenario requirements in ITER and DEMO. The safety standard requirements for protection of the public and release guidelines for tritium have been reviewed. General safety approaches including minimizing tritium inventories, reducing tritium permeation through materials, and decontaminating material for waste disposal have been suggested.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Coupling localized Noah-MP-Crop model with the WRF model improved dynamic crop growth simulation across Northeast China

Croplands play a critical role in regulating the energy and moisture exchanges between the land surface and atmosphere. However, the interactions between cropland and climate are usually poorly represented due to a lack of detailed representation in crop types and field management. Here, we coupled the Noah-MP-Crop model with the state-of-the-art Weather Research and Forecasting (WRF) model to explore and evaluate the crop growth dynamics in response to climate variations across Northeast China. The default parameters of the crop model were not exactly suitable for the agricultural ecosystems in Northeast China. The detailed cropland distribution, and crop phenology parameters including growing degree days (GDD) and planting (harvesting) date were first created using multi-source remote sensing products and reanalysis data, and was then successfully used to simulate the growth and yield for corn and soybean and associated energy exchanges. We also optimized and calibrated other crop parameters using the time-series of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface products. The modified crop model substantially improved the simulation of crop growth, plant physiology, and biomass accumulation for both corn and soybean. Coupling the localized dynamic crop model into the WRF led to considerable decreases in the simulated mean-absolute-errors (MAEs) and biases of the leaf area index, evapotranspiration, and gross primary production compared with the MODIS observed values. Compared with the statistical yield from each province, the modified crop model underestimated the corn yield from 11.1% to 48.6%, whereas overestimated the soybean yield from 16.5% to 162.6%.

54 ENVIRONMENTAL SCIENCES↗