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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Development of a coupled experimental–computational approach for engineering optimization of spout-fluidized bed particle coating systems

The design of spout-fluidized bed (SFB) coating systems for nuclear particle fuels typically relies on trial-and-error processes, comprising iterative and time-consuming coating deposition experiments and post-deposition characterization. At an engineering scale, this approach to guided SFB system design is inefficient, highlighting the need for streamlined experimental methodologies which can correlate fluidization conditions to downstream coating outcomes. In this study, we combine time-resolved particle image velocimetry (PIV) with CFD–DEM simulations to benchmark hydrodynamic behavior in a 3D spout-fluidized bed. By exploiting easily accessible optical measurements of particle motion at the bed wall and within the spouting region, we obtain quantitative velocity fields that can be directly compared with model predictions of the occluded bed region, without resorting to complex imaging and characterization techniques such as X-ray or magnetic resonance tomography. Experimental benchmarking reveals strong agreement between CFD–DEM and PIV in the spout and annulus regions, while discrepancies near the wall highlight areas for future model development. Here, the proposed integrated experimental–numerical framework will enable a direct connection between measured variables and numerically predicted fluidization performance of dense, surrogate nuclear particle fuel feedstock such that experimental SFB component design can be rapidly evaluated, informing design decisions for nozzle geometry and operating conditions. Future work will extend this framework by correlating quantified fluidization metrics across nozzle geometries and operating conditions with the resulting coating morphology, microstructure, and uniformity. Establishing these correlations will enable predictive links between hydrodynamic performance and coating quality, providing a rational, scalable basis for optimizing SFB design prior to coating deposition.

CFD/DEM↗
DOE OSTI2021

Influence of the Anionic Zinc-Adeninate Metal–Organic Framework Structure on the Luminescent Detection of Rare Earth Ions in Aqueous Streams

Rare earth elements (REEs) are critical to numerous technologies; however, a combination of increasing demand, environmental concerns, and monopolistic marketplace conditions has spurred interest in boosting the domestic REE production from sources such as coal utilization byproducts. The economic viability of this approach requires rapid, inexpensive, and sensitive analytical techniques capable of characterizing the REE content during resource exploration and downstream REE processing (e.g., analyzing REE separation, concentration, and purification production steps). Luminescence-based sensors are attractive because many REEs may be sensitized to produce element-specific emission. Hence, a single material may simultaneously detect and distinguish multiple REEs. Metal–organic frameworks (MOFs) can sensitize multiple REEs, but their viability has been hindered by sensitivity and selectivity challenges. Understanding how the MOF structure impacts the REE sensing efficacy is critical to the rational design of new sensors. Here, we evaluate the sensing performance of seven different anionic zinc-adeninate MOFs with different organic linkers and/or structures for the visible-emitting REEs Tb, Dy, Sm, and Eu. The choice of a linker determines which REEs are sensitized and significantly influences their sensitivity and selectivity against competing species (here, Fe(II) and HCl). For a given linker, structural changes to the MOF can further fine-tune the performance. The MOFs produce some of the lowest detection limits (sub-10 ppb for Tb) reported for the aqueous sensitization-based REE detection. Importantly, the most selective MOFs demonstrated the ability to sensitize the REE signal at sub-ppm levels in a REE-spiked acid mine drainage matrix, highlighting their potential for use in real-world sensing applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Quantum computing for finance

Quantum computers are expected to surpass the computational capabilities of classical computers and have a transformative impact on numerous industry sectors. Here, we present a comprehensive summary of the state of the art of quantum computing for financial applications, with particular emphasis on stochastic modelling, optimization and machine learning. This Review is aimed at physicists, so it outlines the classical techniques used by the financial industry and discusses the potential advantages and limitations of quantum techniques. Finally, we look at the challenges that physicists could help tackle. Quantum computers are expected to surpass classical computers and transform industries. This Review focuses on quantum computing for financial applications and provides a summary for physicists on potential advantages and limitations of quantum techniques, as well as challenges that physicists could help tackle.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Entanglement properties of disordered quantum spin chains with long-range antiferromagnetic interactions

Entanglement measures are useful tools in characterizing otherwise unknown quantum phases and indicating transitions between them. Here we examine the concurrence and entanglement entropy in quantum spin chains with random long-range couplings, spatially decaying with a power-law exponent $\textit{α}$. Using the strong disorder renormalization group (SDRG) technique, we find by analytical solution of the master equation a strong disorder fixed point, characterized by a fixed point distribution of the couplings with a finite dynamical exponent, which describes the system consistently in the regime $α > \frac{1}{2}$ . A numerical implementation of the SDRG method yields a power-law spatial decay of the average concurrence, which is also confirmed by exact numerical diagonalization. However, we find that the lowest-order SDRG approach is not sufficient to obtain the typical value of the concurrence. We therefore implement a correction scheme which allows us to obtain the leading-order corrections to the random singlet state. This approach yields a power-law spatial decay of the typical value of the concurrence, which we derive both by a numerical implementation of the corrections and by analytics. Next, using numerical SDRG, the entanglement entropy (EE) is found to be logarithmically enhanced for all $\textit{α}$, corresponding to a critical behavior with an effective central charge $\textit{c}$ = ln(2), independent of $\textit{α}$. This is confirmed by an analytical derivation. Using numerical exact diagonalization (ED), we confirm the logarithmic enhancement of the EE and a weak dependence on $\textit{α}$. For a wide range of partition size $\textit{l}$, the EE fits a critical behavior with a central charge close to $\textit{c}$ = 1, which is the same as for the clean Haldane-Shastry model with a power-law-decaying interaction with $\textit{α}$ = 2. Only for small $l \ll L$, in a range which increases with the number of spins N, we find deviations which are rather consistent with the strong disorder fixed point central charge $\textit{c}$ = ln(2). Furthermore, we find using ED that the concurrence shows power-law decay, albeit with smaller power exponents than obtained by SDRG. Finally, we also present results obtained with DMRG and find agreement with ED for sufficiently small $\textit{α}$ < 2, whereas for larger $\textit{α}$ DMRG tends to underestimate the entanglement entropy and finds a faster decaying concurrence.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Computation of high-frequency magnetoelastic waves in layered materials

Here, the direct calculation of magnetoelastic wave dispersion in layered media is presented using an efficient, accurate computational technique. The governing, coupled equations for elasticity and magnetism, the Navier and Landau-Lifshitz equations, respectively, are linearized to form a quadratic eigenvalue problem that determines a complex web of wave-number–frequency dispersion branches and their corresponding mode profiles. Numerical discretization of the eigenvalue problem via a spectral collocation method (SCM) is employed to determine the complete dispersion maps for both a single, finite-thickness magnetic layer and a finite magnetic-nonmagnetic double-layer. The SCM, previously used to study elastic waves in nonmagnetic media, is fast, accurate, and adaptable to a variety of sample configurations and geometries. Emphasis is placed on the extremely high-frequency regimes being accessed in ultrafast magnetism experiments. The dispersion maps and modes provide insight into how energy propagates through the coupled system, including how energy can be transferred between elastic- and magnetic-dominated waves as well as between different layers. The numerical computations for a single layer are further understood by a simplified analytical calculation in the high-frequency, exchange-dominated regime where the resonance condition required for energy exchange (an anticrossing) between quasi-elastic and quasi-magnetic dispersion branches is determined. Nonresonant interactions are shown to be well approximated by the dispersion of uncoupled elastic and magnetic waves. The methods and results provide fundamental theoretical tools to model and understand current and future magnetic devices powering spintronic innovation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Efficient quadrature rules for finite element discretizations of nonlocal equations

In this paper we design efficient quadrature rules for finite element discretizations of nonlocal diffusion problems with compactly supported kernel functions. Two of the main challenges in nonlocal modeling and simulations are the prohibitive computational cost and the nontrivial implementation of discretization schemes, especially in three-dimensional settings. In this work we circumvent both challenges by introducing a parametrized mollifying function that improves the regularity of the integrand, utilizing an adaptive integration technique, and exploiting parallelization. We first showthat the “mollified” solution converges to the exact one as the mollifying parameter vanishes, then we illustrate the consistency and accuracy of the proposed method on several two- and three-dimensional test cases. Furthermore, we demonstrate the good scaling properties of the parallel implementation of the adaptive algorithm and we compare the proposed method with recently developed techniques for efficient finite element assembly.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Transient cycling of nitrogen, organic carbon and oxygen within the free-flowing Columbia River corridor: Linking exposure time dependent biogeochemical reactions to river stage fluctuations (Final project report)

The objective of this project was to develop next-generation techniques for representing the transformations of complex reaction networks like those impacting transient river-corridors, then apply them to develop upscaling tools. The project contributed significantly to the development of Lagrangian “mass transfer particle tracking” (MTPT) tools that are the first numerical framework that explicitly separates mixing and spreading processes; a crucial distinction for accurate representations of reaction rates across scales. The MTPT approach uses an operator splitting scheme where physical transport processes are simulated using classical random walk methods and each particle is treated as a “container” that carries with it any number of chemical species. Mixing between particles is simulated using a colocation-probability based mass transfer kernel and reactions are evaluated on each particle after mixing. The method is stable, accurate, and also allows the explicit modeling of residence time distributions of the individual containers of mass. The MTPT scheme allowed us to explore several research questions related to reactive transport in river corridors and complex reaction networks. We found that it is possible to quantify the exposure time distributions (ETDs) of reactants and that this does suggest some pathways to upscaling. However, comparable approximations can be obtained using simplified (reduced dimensionality) MTPT simulations in less time with similar uncertainty, so development of extensive ETD-based methods was not productive. The major findings are that i) the MTPT schemes are robust and highly accurate across a range of arbitrarily complex reactions, ii) the methods can be efficiently parallelized and the parallel performance characteristics of MTPT are predictable, and iii) the MTPT tools allow simultaneous tracking of residence time. The development of these research tools into efficient software packages continues. The methods are already available to the community because open-source, working examples have been included with all publications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Collaborative Research: Enabling multi-scale studies of magnetic reconnection with interpretable data-driven models

The development of accurate reduced descriptions and improved closures for magnetic reconnection is an important and a long‐standing challenge in plasma physics. The four‐fluid approach, and associated closures, that were investigated have the potential to improve the accuracy of plasma fluid models, capturing physical effects which would otherwise require a kinetic description. If successful, this approach could have an important impact for the modeling of laboratory and space plasmas. The major goals of this project were to develop new machine learning (ML) tools based on sparse and symbolic regression techniques, and to extract interpretable and generalizable reduced models (e.g., in the form of partial differential equations - PDEs) from data generated by first principles plasma simulations. Preserving interpretability of such data‐driven models is key to addressing the long‐standing theoretical and numerical challenges. Prior proof‐of‐principle studies have demonstrated the enormous potential of this approach, by recovering the well‐established hierarchy of plasma equations (from Vlasov to MHD) from data produced by particle‐in‐cell (PIC) simulations. Our goal in this project was to extend and apply these new tools to construct better kinetic closures for magnetic reconnection; to derive better models of particle injection and acceleration by this fundamental plasma process; and to use this understanding to accelerate the development of multi‐scale plasma algorithms. While our immediate focus was on the problem of magnetic reconnection, the tools that were will developed are general and applicable to other areas of plasma physics, and more broadly to many‐body phenomena. We anticipate that the development of these multi‐scale models will have a significant impact across different areas of plasma science, from fusion to space and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A Missing Puzzle in Dissociative Electron Attachment to Biomolecules: The Detection of Radicals

Ionizing radiation releases a flood of low-energy electrons that often causes the fragmentation of the molecular species it encounters. Special attention has been paid to the electrons’ contribution to DNA damage via the dissociative electron attachment (DEA) process. Although numerous research groups worldwide have probed these processes in the past, and many significant achievements have been made, some technical challenges have hindered researchers from obtaining a complete picture of DEA. Therefore, this research perspective calls urgently for the implementation of advanced techniques to identify non-charged radicals that form from such a decomposition of gas-phase molecules. Having well-described DEA products offers a promise to benefit society by straddling the boundary between physics, chemistry, and biology, and it brings the tools of atomic and molecular physics to bear on relevant issues of radiation research and medicine.

Ptasinska, Sylwia (ORCID:0000000275508189)↗
DOE OSTI2024

Identification of Climatological Representative Days in the Mid-Atlantic for High-Fidelity Offshore Wind Energy Modeling

The goal of reaching 30 GW of offshore wind energy by 2030 becomes more realistic with the continued approval of offshore wind energy areas by the Biden Administration. In the Mid-Atlantic, where wind energy projects are in the most advanced stages of development, there is increased research focus on the eventual interaction of these wind farms. These interactions, in the form of wakes and cluster wakes, or wakes from multiple wind farms, could have detrimental effects on power production and forecastability for downwind wind farms (Pryor et al. 2022, Golbazi et al. 2022, Rosencrans et al. 2023). To help alleviate these issues, numerical simulations in the form of numerical weather prediction (NWP) and large eddy simulations (LES) can provide insight into when cluster wake situations may occur, but running such simulations can be expensive and difficult to run for multiple years. In this study, we leverage and build upon existing techniques in the literature (Fischereit et al. 2022) to identify climatologically representative days for wind energy areas in the Mid-Atlantic where conditions would promote cluster wake situations. We select meteorological variables (wind speed, wind direction, atmospheric stability, boundary-layer height, TKE) critical to understanding wind energy production and wake propagation. We then consider two different NWP datasets of varying spatial and temporal resolution: ERA5 provides data at hourly intervals from 1940 to present at 0.25 deg (31 km) spatial resolution (Hersbach et al. 2020), and the NOW-23 dataset provides data at 5-minute resolution for 21 years at 2-km spatial resolution (Bodini et al. 2020). Our first step is to compare these two datasets for an overlapping 21-year time period. Initial results show that the required number of days to represent the long-term climate increases with each additional variable considered. In their study of the German Bight, Fischereit et al. (2022) found that they could represent the long-term wind and wave climate in a "near-perfect" way with -180 days, by reaching a Perkins Skill Score (PSS) of 0.9; our investigation of the mid-Atlantic wind resource region with ERA5 and NOW-23 data suggests that we will need -100 days to reach a PSS of 0.9. As we expand our parameter space to include multiple variables, the number of required days will likely grow. These results will ultimately be used to select case studies to best represent cluster wake conditions that apply to this region for the lifetime of likely wind farms in this mid-Atlantic region.

clusterwakes↗
DOE OSTI2020

Spatial Mapping of Riverbed Grain-Size Distribution Using Machine Learning

Recent alluvial sediments in riverbeds play a significant role in controlling hydrologic exchange flows (HEFs) in river systems. The alluvial layer is usually associated with strong heterogeneity in physical properties (e.g., permeability and hydraulic conductivity), which affects local HEFs and therefore biogeochemical processes. The spatial distribution of these physical properties needs to be determined to inform the numerical models used to reveal the realistic hydro-biogeochemical behaviors. Such information can be obtained based on the intrinsic link between sediment grain-size distribution and hydraulic properties where sediment texture information is available. However, grain-size measurements are usually spatially sparse and do not have adequate coverage and resolution, particularly for a relatively large domain such as the Hanford Reach of the Columbia River. In this paper, we adopted machine learning (ML) approaches for categorizing and mapping the spatial distributions of riverbed substrate grain size and filling in missing areas of substrate data using the ML models along the reach. Such ML models for substrate size mapping were trained at 13,372 locations using measured substrate sizes along with observed and simulated attributes, including bathymetric attributes (e.g., elevation, slope, and aspect ratio) from LIDAR and bathymetric surveys, and hydrodynamic properties (e.g., water depth, velocity, shear stress, and their statistical moments). An ensemble bagging-based ML technique, Random Forest, was adopted to identify the most influential factors as predictors to develop the predictive models with over-fitting issues addressed. The models were evaluated with respect to each individual substrate size class and the lumped group, and then used to generate the final substrate size maps covering all the grid cells in the numerical modeling domain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Real-Frequency Response Functions at Finite Temperature

Building on previous developments [A. Taheridehkordi, S. H. Curnoe, and J. P. F. LeBlanc, Phys. Rev. B 99, 035120 (2019); A. Taheridehkordi, S. H. Curnoe, and J. P. F. LeBlancPhys. Rev. B101, 125109 (2020); A. Taheridehkordi, S. H. Curnoe, and J. P. F. LeBlancPhys. Rev. B102, 045115 (2020), B. Holm and U. von Barth, Phys. Rev. B 57, 2108 (1998), J. Vičičevic and M. Ferrero, Phys. Rev. B 101, 075113 (2020)], we show that the diagrammatic Monte Carlo technique allows us to compute finite-temperature response functions directly on the real-frequency axis within any field-theoretical formulation of the interacting fermion problem. There are no limitations on the type and nature of the system’s action or whether partial summation and self-consistent treatment of certain diagram classes are used. In particular, by eliminating the need for numerical analytic continuation from a Matsubara representation, our scheme allows us to study spectral densities of arbitrary complexity with controlled accuracy in models with frequency-dependent effective interactions. Finally, for illustrative purposes we consider the problem of the plasmon linewidth in a homogeneous electron gas (jellium).

3-dimensional systems↗
DOE OSTI2021

Direct Optoelectronic Imaging of 2D Semiconductor–3D Metal Buried Interfaces

The semiconductor-metal junction is one of the most critical factors for high performance electronic devices. In two-dimensional (2D) semiconductor devices, minimizing voltage drop at this junction is of particularly challenging and important. Despite numerous studies on contact resistance in 2D semiconductors, the exact nature of the buried interface under a 3D metal remains elusive and unclear. Herein, we report the direct observation of 2D semiconductor-metal buried interface using recently developed metal-assisted transfer technique to expose the buried interface which is then directly investigated using scanning probe techniques. We characterize the spatially varying electronic and optical properties of this buried interface with < 20 nm resolution. To be specific, potential, conductance and photoluminescence at the buried metal/MoS 2 interface are correlated under variety of metal deposition conditions as well as type of metal contacts. We observe that direct evaporation of Au on MoS 2 induces large strain of ~5% in the MoS 2 which coupled with charge transfer leads to degenerate doping of the MoS 2 underneath the contact. These factors lead to improvement of contact resistance to record values of 138 kΩ μm measured using local conductance probes. This approach was adopted to investigate MoS 2 -In/Au alloy interface, which records lowest contact resistance of 63 kΩ μm. Overall, our results highlight that the MoS 2 /Metal interface is very sensitive to method of contact making and provides a universal strategy to characterize buried contact interfaces involving 2D semiconductors.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Efficient prediction of attosecond two-colour pulses from an X-ray free-electron laser with machine learning

Abstract X-ray free-electron lasers are sources of coherent, high-intensity X-rays with numerous applications in ultra-fast measurements and dynamic structural imaging. Due to the stochastic nature of the self-amplified spontaneous emission process and the difficulty in controlling injection of electrons, output pulses exhibit significant noise and limited temporal coherence. Standard measurement techniques used for characterizing two-coloured X-ray pulses are challenging, as they are either invasive or diagnostically expensive. In this work, we employ machine learning methods such as neural networks and decision trees to predict the central photon energies of pairs of attosecond fundamental and second harmonic pulses using parameters that are easily recorded at the high-repetition rate of a single shot. Using real experimental data, we apply a detailed feature analysis on the input parameters while optimizing the training time of the machine learning methods. Our predictive models are able to make predictions of central photon energy for one of the pulses without measuring the other pulse, thereby leveraging the use of the spectrometer without having to extend its detection window. We anticipate applications in X-ray spectroscopy using XFELs, such as in time-resolved X-ray absorption and photoemission spectroscopy, where improved measurement of input spectra will lead to better experimental outcomes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

2-D seismic wave propagation using the distributional finite-difference method: further developments and potential for global seismology

SUMMARY We present a time-domain distributional finite-difference scheme based on the Lebedev staggered grid for the numerical simulation of wave propagation in acoustic and elastic media. The central aspect of the proposed method is the representation of the stresses and displacements with different sets of B-splines functions organized according to the staggered grid. The distributional finite-difference approach allows domain-decomposition, heterogeneity of the medium, curvilinear mesh, anisotropy, non-conformal interfaces, discontinuous grid and fluid–solid interfaces. Numerical examples show that the proposed scheme is suitable to model wave propagation through the Earth, where sharp interfaces separate large, relatively homogeneous layers. A few domains or elements are sufficient to represent the Earth’s internal structure without relying on advanced meshing techniques. We compare seismograms obtained with the proposed scheme and the spectral element method, and we show that our approach offers superior accuracy, reduced memory usage, and comparable efficiency.

Geochemistry & Geophysics↗
DOE OSTI2021

Imaging the short-lived hydroxyl-hydronium pair in ionized liquid water

The radiolysis of water is ubiquitous in nature and plays a critical role in numerous biochemical and technological applications. Although the elementary reaction pathways for the ionized water have been studied, the short-lived intermediate complex and structural dynamic response after the proton transfer reaction remain poorly understood. Here, using liquid-phase ultrafast electron diffraction technique to measure the intermolecular O··O and O··H bonds, we captured the short-lived radical-cation complex OH(H 3 O + ) that was formed within 140 femtoseconds through a direct oxygen-oxygen bond contraction and proton transfer, followed by the radical-cation pair dissociation and the subsequent structural relaxation of water within 250 femtoseconds. These measurements provide direct evidence of capturing this metastable radical-cation complex before separation, thereby improving our fundamental understanding of elementary reaction dynamics in ionized liquid water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Roadmap to Advance Heliostat Technologies for High Temperature Solar-Thermal Systems

Since its establishment, the Heliostat Consortium (HelioCon) has made substantial progress toward closing many of the gaps in concentrating solar power (CSP) research. Numerous techno-economic studies have been performed, investigating topics ranging from the trade-off between size and temperature for industrial process heat applications to optimization of the heliostat design itself for various applications. Significant improvements have been made in optical metrology techniques, with first steps toward in situ measurement of heliostat fields. Several standards have been, and continue to be, developed with the coordination of an international group of CSP industry participants. Training programs have been developed, with universities including CSP in their engineering curricula, and many public webinars have been held to provide broad access to the latest CSP research. Improved CSP components such as mirror facets and wireless communication systems have been developed, and the solar tower at Sandia National Laboratories has been upgraded with a testbed for closed-loop controls research and development. Field deployment challenges involving heliostat foundations and sensitive wildlife habitats have been explored, with progress made toward methods for streamlining project development and permitting. Additional knowledge has been added to the body of work on wind behavior of heliostats and arrays of heliostats, with progress made toward a holistic understanding of wind design methods. Finally, techniques have been developed and demonstrated for assessing soiling conditions at a proposed project site, with predictive models for the soiling rate showing good results. Taking these results together, HelioCon has contributed greatly to the global CSP research and development effort over the past several years.

14 SOLAR ENERGY↗
DOE OSTI2021

Compaction of crushed salt for safe containment – overview of the KOMPASS project

Abstract. In Germany, rock salt formations are possible host rock candidates for a repository for heat-emitting radioactive waste. The safety concept of a repository in salt bases on a multibarrier system consisting mainly of the geological barrier salt and geotechnical seals ensuring safe containment. Crushed salt will be used for backfilling of cavities and sealing measures in drifts and shafts due to its favourable properties and its easy availability (mined-off material). The creep of the rock salt leads to crushed salt compaction with time. Thereby, the crushed salts' porosity is reduced from the initial porosity of 30 %–40 % to a value comparable to the porosity of undisturbed rock salt (≤1 %). In such low porosity ranges, technical impermeability is assumed. The compaction behaviour of crushed salt is rather complex and involves several coupled THM processes (Kröhn et al., 2017; Hansen et al., 2014). It is influenced by internal properties like humidity and grain size distribution, as well as boundary conditions such as temperature, compaction rate or stress state. However, the current process understanding has some important gaps referring to the material behaviour, experimental database and numerical modelling. It needs to be extended and validated, especially in the low porosity range. The objective of the KOMPASS project was development of methods and strategies for the reduction of deficits in the prediction of crushed salt compaction leading to an improvement of the prognosis quality. Key results are as follows (KOMPASS Phase 1, 2020): selection of an easily available and permanently producible synthetic crushed salt mixture, acting as a reference material for generic investigations; development and proof of different techniques for producing pre-compacted samples for further investigations; establishment of a tool of microstructure investigation methods to demonstrate the comparability of grain structures of pre-compacted samples with in-situ compacted material for future investigations; execution of various laboratory experiments using pre-compacted samples, e.g. long-term creep tests which deliver reliable information about time- and stress-dependent compaction behaviour; development of a complex experimental investigation strategy to derive necessary model parameters considering individual functional dependencies. Its technical feasibility was successfully verified; benchmarking with various existing numerical models using datasets from three different triaxial long-term tests. The result was not entirely satisfactory; however, the number of influencing factors is small and further validation work has to be done. Overall, the KOMPASS project has made significant progress in the approaches to solving the outstanding question, building the basis for further investigations.

Friedenberg, Larissa↗