Hasil untuk "Dynamic and structural geology"

Bartłomiej Bosek, Jadwiga Czyżewska, Evangelos Kipouridis et al.

We present a dynamic data structure for representing binary $n\times n$ matrices that are $d$-twin-ordered, for a~fixed parameter $d$. Our structure supports cell queries and single-cell updates both in $\Oh(\log \log n)$ expected worst case time, while using $\Oh_d(n)$ memory; here, the $\Oh_d(\cdot)$ notation

Hidemasa Bessho, Takeshi Kawasaki, Hayato Shiba

In this study, we demonstrate the generalizability of graph neural networks in predicting the dynamic heterogeneity of model glass-forming liquids across different temperatures. While previous approaches have often been limited to making predictions at the specific temperatures used during training, we find that our proposed framework - T-BOTAN - enables interpolation to temperatures not included in the training set. We show that the dynamical behavior, the associated four-point correlations, and even the macroscopic temperature can be estimated with sufficient accuracy solely from static particle configurations at untrained temperatures. These results suggest that static configurations encode not only local structural features driving dynamic heterogeneity but also fundamental thermodynamic information.

Degterev, Artem V., Chibisova, Marina V.

In 2024, 616 ash emissions were registered at Ebeko volcano (Paramushir Island, Northern Kurils) to heights from 1.5 to 4.5 km above sea level (181 of them reached a height of 3 km or more). The distribution of emission frequency and height during the year turned out to be unusual compared to the periods 2018–2021 and 2022–2023. The period from February to April was characterized by increased explosive activity: the total number of emissions and their maximum height significantly exceeded the values of the same months of the previous years. From May to September, on the contrary, the eruptive activity significantly decreased relative to the average values of 2018–2021 and 2022–2023 (previously, the peak activity occurred during the summer months, when more than 100 events per month could be registered). From October 2024, a further decrease in the height and frequency of emissions, as well as a decrease in the concentration of ash in eruptive clouds, has been recorded. The last vapor-gas emission with insignificant ash content occurred on January 16, 2025. The pause in the activity of the Ebeko volcano since mid-January 2025 still maintains the need for continuous monitoring, given its high activity in recent years and its proximity to the settlement.

Gregor Hillers, Emilia Koivisto, Päivi Haapanala et al.

We report on establishing the mobile Finnish Seismic Instrument Pool (FINNSIP) that is owned and operated by Finnish academic and research institutions. The pool supports domestic and international collaborative seismic research. At the conclusion of the 2020 to 2024 build-up stage, the instrumentation includes 46 broadband seismometers and digitizers, 5 accelerometers, and 1216 and 71 Geospace and SmartSolo autonomous geophone units, respectively, making FINNSIP one of the largest and most coherent mobile seismic instrument pools in Europe in the public sector. We explain the utilization of the pool instruments and discuss the equipment, facilities, ownership and governance structure, fees, and the management and support system. Through Finland's membership in the Observatories and Research Facilities for European Seismology (ORFEUS) and the Finnish European Plate Observing System (EPOS) node, FINNSIP endorses and implements international data management standards and best practices as promoted in Europe. The importance of appropriate data and computing systems is highlighted by the ~90 TB volume of formatted data that has been collected in 25 large-N projects between October 2021 and December 2024. We summarize a checklist for building, operating, and managing this extensive seismic pool that can inform the planning and establishment of other research infrastructure.

Nate Soule, Paul Santi

Two properties that are commonly used in the analysis of debris-flow motion and behavior are viscosity and yield strength; however, many of the techniques to measure these properties are tedious, highly theoretical, and use only the finer fraction of debris. The purpose of this study is to develop a practical and consistent method of determining the influence that coarse particles, up to 25.4 mm, have on the viscosity and yield strength of debris flows, using more accessible testing methods. Samples were tested at various sediment concentrations and with increasing maximum grain sizes of particles. Values for viscosity and yield strength of each mixture were measured and compared using four separate, previously derived laboratory tests: an inclined flume box, a slump test, a simple inclined plane, and a rolling sleeve viscometer. The slump test and rolling sleeve viscometer produced the most consistent and reasonable results, particularly as the maximum grain size was increased. In general, the sediment concentration required to produce a given yield strength increased as coarser particles were added to a slurry. While viscosity changes with grain size distribution, its variation can be predicted by sediment concentration alone. Both yield strength and viscosity could be predicted from the finer fraction of sediment, and a proposed method to predict the addition of coarse material is described. Including coarse material, yield strength and viscosity values are expected to be within 25 and 100%, respectively, of values measured by other methods.

António M. G. Pedro, Paulino Dias Santos, Luís Araújo Santos et al.

This paper discusses the principal sources of uncertainty in the execution and interpretation of Bender Element (BE) tests conducted on reconstituted sand samples. Based on the experience accumulated by the Geotechnical Laboratory of the University of Coimbra, the study addresses three critical stages of the testing process: sample preparation, test execution, and result interpretation. For each stage, the key challenges are identified, and potential solutions are proposed. Particular emphasis is placed on the control of relative density and sample saturation during preparation, as well as on factors affecting signal quality and time lag of the system during test execution. The interpretation of the results is analyzed with respect to the limitations of currently employed methods. The overall reliability of the procedures employed throughout the testing process is also assessed, with the results providing guidance for improving the accuracy and consistency of BE test outcomes.

Lucas Arsenith, Grant Goertzen, Nick Hudyma

Rockfall poses a significant hazard in steep terrain, where complex ground interactions cause falling boulders to deviate from straight-line paths. While lateral dispersion is commonly used to describe the distribution of deposited boulders from rockfall events, it does not provide any insight into the complexity of boulder trajectories while in motion. This study introduces tortuosity, a metric typically applied in porous media hydraulic analysis, as a novel approach for quantifying the deviation of rockfall paths from linearity. Using high-resolution UAV-based LiDAR data and RocFall3 (Version 1.017) simulation software, this research investigates the effects of terrain model resolution, boulder shape, and boulder mass on tortuosity values for 20,000 simulated rockfalls on a columnar jointed basalt slope in Boise, ID, USA. Results show that increasing terrain resolution leads to higher tortuosity values due to the increased presence of terrain asperities. Spherical boulders exhibited higher tortuosity than hexagonal ones, and tortuosity decreased with increasing mass for spheres, likely due to their momentum overcoming minor terrain features. Hexagonal boulders, constrained by their angular shape, showed less variability in tortuosity across resolutions and sizes. These findings emphasize the limitations of low-resolution publicly available LiDAR data and highlight the critical influence of accurate boulder representation in simulation models.

Marco Peruzzo, Giacomo Baggio, Francesco Ticozzi

We consider a network of identical, first-order linear systems, and investigate how replacing a subset of the systems composing the network with higher-order ones, either taken to be generic or specifically designed, may affect its controllability. After establishing a correspondence between state controllability in networks of first-order systems with output controllability in networks of higher-order systems, we show that adding higher-order dynamics may require significantly fewer subsystem modifications to achieve structural controllability, when compared to first-order heterogeneous subsystems. Furthermore, we characterize the topology of networks (which we call X-networks) in which the introduction of heterogeneous local dynamics is not necessary for structural output controllability, as the latter can be attained by suitable higher-order subsystems with homogeneous internal dynamics.

Miyuki T. Nakata

Understanding learning as a dynamic process is challenging due to the interaction of multiple factors, including cognitive load, internal state change, and subjective evaluation. Existing approaches often address these elements in isolation, limiting the ability to describe learning phenomena within a unified and structurally explicit framework. This paper proposes a multi-layer formal descriptive framework for learning dynamics. Rather than offering a predictive or prescriptive model, the framework introduces a symbolic language composed of state variables, mappings, and layer-specific responsibilities, enabling consistent description of learning processes without commitment to specific functional forms or optimization objectives. This descriptive framework is intended to serve as a structural substrate for analyzing learning processes in human learners, and by extension, in adaptive and Al-assisted learning systems. A central design principle is the explicit separation of descriptive responsibilities across layers, distinguishing load generation, internal understanding transformation, observation, and evaluation. Within this structure, cognitive load is treated as a relational quantity arising from interactions between external input and internal organization, while subjective evaluation is modeled as a minimal regulatory interface responding to learning dynamics and environmental conditions. By emphasizing descriptive clarity and extensibility, the framework provides a common language for organizing existing theories and supporting future empirical and theoretical work.

Sicheng Wang, Shuhao Chen, Jingran Zhou et al.

Global food trade plays a crucial role in ensuring food security and maintaining supply chain stability. However, its network structure evolves dynamically under the influence of geopolitical, economic, and environmental factors, making it challenging to model and predict future trade links. Effectively capturing temporal patterns in food trade networks is therefore essential for improving the accuracy and robustness of link prediction. This study introduces IVGAE-TAMA-BO, a novel dynamic graph neural network designed to model evolving trade structures and predict future links in global food trade networks. To the best of our knowledge, this is the first work to apply dynamic graph neural networks to this domain, significantly enhancing predictive performance. Building upon the original IVGAE framework, the proposed model incorporates a Trade-Aware Momentum Aggregator (TAMA) to capture the temporal evolution of trade networks, jointly modeling short-term fluctuations and long-term structural dependencies. A momentum-based structural memory mechanism further improves predictive stability and performance. In addition, Bayesian optimization is used to automatically tune key hyperparameters, enhancing generalization across diverse trade scenarios. Extensive experiments on five crop-specific datasets demonstrate that IVGAE-TAMA substantially outperforms the static IVGAE and other dynamic baselines by effectively modeling temporal dependencies, while Bayesian optimization further boosts performance in IVGAE-TAMA-BO. These results highlight the proposed framework as a robust and scalable solution for structural prediction in global trade networks, with strong potential for applications in food security monitoring and policy decision support.

Kamal G. Soni, Jayraj P. Anadani, Mitanshu B. Vahiya et al.

Zr-Cu-Al alloys belong to a commercially important family of CuZr-based alloys that form bulk metallic glasses on microalloying of Al. However, the identification of compositions with good glass-forming ability and desirable properties from a vast compositional space remains a major challenge due to complex compositional effects on the structure, dynamics and properties. In the present work, we report molecular dynamic investigations of structure, dynamics, thermodynamic and mechanical properties of Zr$_{50}$Cu$_{50-x}$Al$_x$ and Cu$_{50}$Zr$_{50-x}$Al$_x$ alloys ($x=5,10,15,20,25,30,40$) covering a wide compositional space. Our results and findings lead to some important conclusions that could serve as overarching guidelines for choosing good glass-forming alloy compositions that give Zr-Cu-Al glasses with tailored thermal and mechanical properties. Overall, present results suggest that a good glass-forming Zr-Cu-Al alloy composition leading to an MG with good thermal and mechanical properties should be Cu-rich with Zr concentration in the window 30\%-35\% and Al\% > 20. Our results also highlight the impact of icosahedral short- and medium-range ordering on the dynamics and mechanical properties of the alloys. It is observed that the fractions of the full icosahedra $\langle 0,0,12,0 \rangle$ and the degree of their interconnectivity are directly correlated to the structural relaxation, diffusion, dynamic heterogeneity and mechanical properties.

Michael P. H. Stumpf

FlowClass.jl is a Julia package for classifying continuous-time dynamical systems into a hierarchy of structural classes: Gradient, Gradient-like, Morse-Smale, Structurally Stable, and General. Given a vector field \(\mathbf{F}(\mathbf{x})\) defining the system \(\mathrm{d}\mathbf{x}/\mathrm{d}t = \mathbf{F}(\mathbf{x})\), the package performs a battery of computational tests -- Jacobian symmetry analysis, curl magnitude estimation, fixed point detection and stability classification, periodic orbit detection, and stable/unstable manifold computation -- to determine where the system sits within the classification hierarchy. This classification has direct implications for qualitative behaviour: gradient systems cannot oscillate, Morse-Smale systems are structurally stable in less than 3 dimensions, and general systems may exhibit chaos. Much of classical developmental theory going back to Waddington's epigenetic landscape rests on an implicit assumption of gradient dynamics. The package is designed with applications in systems and developmental biology in mind, particularly the analysis of gene regulatory networks and cell fate decision models in the context of Waddington's epigenetic landscape. It provides tools to assess whether a landscape metaphor is appropriate for a given dynamical model, and to quantify the magnitude of non-gradient (curl) dynamics.

M. Breil, M. Breil, F. Krawczyk et al.

<p>Afforestation is an important mitigation strategy for climate change due to its carbon sequestration potential. Besides this favorable biogeochemical effect on global CO<span class="inline-formula">₂</span> concentrations, afforestation also affects the regional climate by changing the biogeophysical land surface characteristics. In this study, we investigate the effects of an idealized global CO<span class="inline-formula">₂</span> reduction to pre-industrial conditions by a Europe-wide afforestation experiment on the regional longwave radiation balance, starting in the year 1986 on a continent entirely covered with grassland. Results show that the impact of biogeophysical processes on the surface temperatures is much stronger than that of biogeochemical processes. Furthermore, biogeophysically induced changes of the surface temperatures, atmospheric temperatures, and moisture concentrations are as important for the regional longwave radiation balance as the global CO<span class="inline-formula">₂</span> reduction. While the outgoing longwave radiation is increased in winter, it is reduced in summer. In terms of annual total, a Europe-wide afforestation has a regional warming effect despite reduced CO<span class="inline-formula">₂</span> concentrations. Thus, even for an idealized reduction of the global CO<span class="inline-formula">₂</span> concentrations to pre-industrial levels, the European climate response to afforestation would still be dominated by its biogeophysical effects.</p>

T. E. Palmer, C. F. McSweeney, B. B. B. Booth et al.

<p>We have created a performance-based assessment of CMIP6 models for Europe that can be used to inform the sub-selection of models for this region. Our assessment covers criteria indicative of the ability of individual models to capture a range of large-scale processes that are important for the representation of present-day European climate. We use this study to provide examples of how this performance-based assessment may be applied to a multi-model ensemble of CMIP6 models to (a) filter the ensemble for performance against these climatological and processed-based criteria and (b) create a smaller subset of models based on performance that also maintains model diversity and the filtered projection range as far as possible.</p> <p>Filtering by excluding the least-realistic models leads to higher-sensitivity models remaining in the ensemble as an emergent consequence of the assessment. This results in both the 25th percentile and the median of the projected temperature range being shifted towards greater warming for the filtered set of models. We also weight the unfiltered ensemble against global trends. In contrast, this shifts the distribution towards less warming. This highlights a tension for regional model selection in terms of selection based on regional climate processes versus the global mean warming trend.</p>

Ivan A. Panteleev, Vladimir I. Okunev, Victor A. Novikov

According to the stick-slip model, the relative movement of the fault planes is an act of unstable sliding, where movement begins when the stresses tangential to the fault plane reach a certain limit. The physical mechanism of dynamic slip along a fault consists of the sequential formation of conglomerates of loaded particles (force chains) in the contact zone and their subsequent destruction. These chains together form a force skeleton characterized by a specific spatial structure and strength properties. An increase in shear stress on the fault banks leads to local destruction of the strength skeleton; further evolution of the system brings destruction processes to higher spatial levels, ultimately leading to a shift in the fault banks. Since the evolution of the process of destruction of force chains in the contact zone of a fault along the hierarchy of scales from bottom to top is similar to the evolution of crack formation in a loaded medium from microscale to macroscale (specimen scale), the authors hypothesized the coherent behavior of acoustic noise accompanying the preparation of dynamic slip and recorded in different areas of fault zones. This work is devoted to testing this hypothesis on a laboratory scale, using an installation that simulates movement along a fault. As a result of the analysis, the hypothesis about the synchronization of the statistical properties of the acoustic emission during the preparation and implementation of the dynamic movement was confirmed. It is shown that the observation (detection) of the effect of the synchronization of the statistical properties of acoustic emission depends both on the set of parameters for which the spectral coherence measure is calculated and on the location of the recording of the initial data.

Mohit Sharma, Manoj Kumar Nandi, Sarika Maitra Bhattacharyya

We present the study of the structure-dynamics correlation for systems interacting via attractive Lennard- Jones and its repulsive counterpart, the WCA potentials. The structural order parameter (SOP) is related to the microscopic mean-field caging potential. At a particle level, the SOP shows a distribution. Although the two systems have similar pair structures, their average SOP differs. However, this difference alone is insufficient to explain the well known slowing down of the dynamics in LJ system at low temperatures. The slowing down can be explained in terms of a stronger coupling between the SOP and the dynamics. To understand the origin of this system specific coupling, we study the difference in the microscopic structure between the hard and soft particles. We find that for the LJ system, the structural differences of the hard and soft particles are more significant and have a much stronger temperature dependence compared to the WCA system. Thus the study suggests that attractive interaction creates more structurally different communities. This broader difference in the structural communities is probably responsible for stronger coupling between the structure and dynamics. Thus the system specific structure-dynamics correlation, which also leads to a faster slowing down in the dynamics, appears to have a structural origin. A comparison of the predictive power of our SOP with the local energy and two body excess entropy shows that in the LJ system, the dynamics is driven by enthalpy, whereas in the WCA system, it is driven by entropy, and our SOP can capture both these contributions.

Jared Suchan, Shahid Azam

An assessment of evaporation losses from soils is critical for sustainable agriculture in semi-arid regions. The purpose of this research was to determine the effect of desaturation and shrinkage on evaporative flux from representative soils. Results indicated that the surface area did not change for silty sand (6% volume reduction) and substantially increased for lean clay (17% volume reduction). The evaporative flux for silty sand decreased from 31 to 25 mg/m²∙s in <i>Stage II</i>, remained constant during <i>Stage III</i>, and decreased to 11 mg/m²∙s in <i>Stage IV</i>. In contrast, the lean clay showed a longer <i>Stage II</i> (34 to 14 mg/m²∙s), a near constant <i>Stage III</i>, albeit a similar <i>Stage IV</i> (13 to 3 mg/m²∙s). The air entry and residual suction values were 1 kPa and 100 kPa for silty sand and 5 kPa and 1400 kPa for lean clay. In both soils, the total suction merged with the matric suction at <i>Stage II</i>–<i>Stage III</i> boundary. Furthermore, the shrinkage curve was J-shaped for silty sand with the only void ratio decrease in <i>Stage II</i>, whereas that for the lean clay showed a significant void ratio decrease in <i>Stage II</i>, marginal decrease in <i>Stage III</i>, and no decrease in <i>Stage IV</i>. Under high demand, the silty sand exhibited <i>Stage III</i> and <i>Stage IV</i> evaporation, whereas the lean clay also showed significant flux during <i>Stage II</i>. For the investigated range of water content, the total water loss under high demand was found to be 7 times that under low demand.

Kai Gong, Elsa Olivetti

Establishing the composition-structure-property relationships for amorphous materials is critical for many important natural and engineering processes, including the dissolution of highly complex volcanic glasses. In this investigation, we performed force field molecular dynamics (MD) simulations to generate detailed structural representations for ten natural CaO-MgO-Al2O3-SiO2-TiO2-FeO-Fe2O3-Na2O-K2O glasses with compositions ranging from rhyolitic to basaltic. Based on the resulting atomic structural representations at 300 K, we have calculated the partial radial distribution functions, nearest interatomic distances and coordination number, which are consistent with the literature data on silicate-based glasses. Based on these structural attributes and classical bond valence models, we have introduced a novel structural descriptor, i.e., average metal-oxygen (M-O) bond strength parameter, which has captured the log dissolution rates of the ten glasses at both acidic and basic conditions (based on literature data) with R2 values of ~0.80-0.92 based on linear regression. This structural descriptor is seen to outperform several other structural descriptors also derived from MD simulation results, including the average metal oxide dissociation energy, the average self-diffusion coefficient of all the atoms at their melting points, and the energy barrier of self-diffusion. Furthermore, we showed that the MD-derived descriptors generally exhibit better predictive performance than the degree of depolymerization parameter commonly used to describe glass and mineral reactivity. The results suggest that the structural descriptors derived from MD simulations, especially the average M-O bond strength parameter, are promising structural descriptors for connecting composition with dissolution rates of highly complex natural glasses.

U. Ehret, Rik van Pruijssen, Marina Bortoli et al.

Abstract. In this paper we propose adaptive clustering as a new method for reducing the computational efforts of distributed modelling. It consists of identifying similar-acting model elements during runtime, clustering them, running the model for just a few representatives per cluster, and mapping their results to the remaining model elements in the cluster. Key requirements for the application of adaptive clustering are the existence of (i) many model elements with (ii) comparable structural and functional properties and (iii) only weak interaction (e.g. hill slopes, subcatchments, or surface grid elements in hydrological and land surface models). The clustering of model elements must not only consider their time-invariant structural and functional properties but also their current state and forcing, as all these aspects influence their current functioning. Joining model elements into clusters is therefore a continuous task during model execution rather than a one-time exercise that can be done beforehand. Adaptive clustering takes this into account by continuously checking the clustering and re-clustering when necessary. We explain the steps of adaptive clustering and provide a proof of concept at the example of a distributed, conceptual hydrological model fit to the Attert basin in Luxembourg. The clustering is done based on normalised and binned transformations of model element states and fluxes. Analysing a 5-year time series of these transformed states and fluxes revealed that many model elements act very similarly, and the degree of similarity varies strongly with time, indicating the potential for adaptive clustering to save computation time. Compared to a standard, full-resolution model run used as a virtual reality “truth”, adaptive clustering indeed reduced computation time by 75 %, while modelling quality, expressed as the Nash–Sutcliffe efficiency of subcatchment runoff, declined from 1 to 0.84. Based on this proof-of-concept application, we believe that adaptive clustering is a promising tool for reducing the computation time of distributed models. Being adaptive, it integrates and enhances existing methods of static grouping of model elements, such as lumping or grouped response units (GRUs). It is compatible with existing dynamical methods such as adaptive time stepping or adaptive gridding and, unlike the latter, does not require adjacency of the model elements to be joined. As a welcome side effect, adaptive clustering can be used for system analysis; in our case, analysing the space–time patterns of clustered model elements confirmed that the hydrological functioning of the Attert catchment is mainly controlled by the spatial patterns of geology and precipitation.

M. Correia, V. Botechia, L. Pires et al.

Summary The significant world oil reserves related to fractured karst reservoirs in Brazilian pre-salt fields adds new frontiers to the (1) development of numerical methods for upscale giant fields with multiscale heterogeneities, (2) history matching and production strategy optimization under critical uncertainties and (3) forecast of the future reservoir performance. However, there is a lack of benchmark models with a heterogeneous dynamic behavior typical from fractured karst reservoirs, to develop and validate novel numerical methods. This work presents a simulation benchmark model, available as public domain data, which represents a fractured carbonate karst reservoir and add a great opportunity to test new methodologies for reservoir development and management using numerical simulation. The work structure is divided in three steps: (1) development of a reference model, a fine grid model with high level of geologic details, treated as the real field, (2) development of a simulation model under uncertainties considering an initial stage of the field development phase, and, (3) elaboration of a benchmark proposal for studies related to the oil field development and production strategy selection. Based on the available information from well logs, several uncertainty attributes were considered in structural framework, facies and petrophysical properties. Dynamic, economic and technical uncertainties were also considered. The reference model is a giant field divided by two stratigraphic zones - the upper zone characterized by stromatolites and the lower one by coquinas. Moreover, the model is characterized by two regions with karst features near the horizons surfaces and a cluster of fractures near faults. Volcanic rocks and high permeable trends near faults are included as non-mapped uncertainties in the simulation model, as the information from well logs at the initial stage of field development does not intercept this geologic attribute. This approach will lead to several challenges on reservoir development and management. As this benchmark is representative of a giant field, it is divided in four sectors. Sector 1 has already a production strategy defined, aiming studies regarding field management. The strategy considers WAG (water alternate gas/CO2) as recovery mechanism and the presence of 13 wells in a first wave (6 producers and 7 injectors), and other 4 wells can be added in a second wave. Field development studies can be applied in the other sectors. This Benchmark provides a great opportunity for develop and test novel numerical methods in giant reservoirs with geologic and dynamic pre-salt trends.