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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

ThunderSecure: deploying real-time intrusion detection for 100G research networks by leveraging stream-based features and one-class classification network

Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks (40/100G) across distributed sites for processing, storage, and analysis. Like general purpose networks, research networks experience intrusions. However, monitoring anomalies in such high-speed network traffics is challenging given current cyber-infrastructure. Moreover, traditional network intrusion detection systems (NIDS) are signature based. However, anomaly patterns are difficult to define and that rulesets are often not updated frequently enough to reflect the changes of attack behaviors. We present ThunderSecure, a high-throughput, unsupervised learning-based intrusions detection system for 100G research networks. ThunderSecure implements an efficient packet processing and detection pipeline using multi-cores and GPUs. It extracts statistical and temporal features from real-time network data streams and feeds them to a one-class anomaly detection network. A baseline of normal distribution will be created based on the training observation. Testing traffic deviated from the learned profile will be marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets mirrored from two 100G network connections at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. Results show that ThunderSecure can recognize science data traffic captured long after the training and made nearly certain detection on the segment of the streams where anomalous flows were injected.

100G research network↗
DOE OSTI2021

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA

Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O 2 reduction and denitrification (NO 3 – reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwater age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF 6 , CFCs, 3 H, He from 3 H (tritiogenic He), 14 C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO 3 – and dissolved gas data to estimate zero order and first order rates of O 2 reduction and denitrification. Results indicated that O 2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O 2 and NO 3 – reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O 2 reduction rates. Estimated historical NO 3 – trends were similar to historical measurements. Here, results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O 2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Inferring the Energy and Distance Distributions of Fast Radio Bursts Using the First CHIME/FRB Catalog

Abstract Fast radio bursts (FRBs) are brief, energetic, typically extragalactic flashes of radio emission whose progenitors are largely unknown. Although studying the FRB population is essential for understanding how these astrophysical phenomena occur, such studies have been difficult to conduct without large numbers of FRBs and characterizable observational biases. Using the recently released catalog of 536 FRBs published by the Canadian Hydrogen Intensity Mapping Experiment/Fast Radio Burst (CHIME/FRB) collaboration, we present a study of the FRB population that also calibrates for selection effects. Assuming a Schechter function, we infer a characteristic energy cut-off of E char = 2.38 − 1.64 + 5.35 × 10 41 erg and a differential power-law index of γ = − 1.3 − 0.4 + 0.7 . Simultaneously, we infer a volumetric rate of [ 7.3 − 3.8 + 8.8 (stat.) − 1.8 + 2.0 ( sys . ) ] × 10 4 Gpc −3 yr −1 above a pivot energy of 10 39 erg and below a scattering timescale of 10 ms at 600 MHz, and find we cannot significantly constrain the cosmic evolution of the FRB population with star-formation rate. Modeling the host’s dispersion measure (DM) contribution as a log-normal distribution and assuming a total Galactic contribution of 80 pc cm −3 , we find a median value of DM host = 84 − 49 + 69 pc cm −3 , comparable with values typically used in the literature. Proposed models for FRB progenitors should be consistent with the energetics and abundances of the full FRB population predicted by our results. Finally, we infer the redshift distribution of FRBs detected with CHIME, which will be tested with the localizations and redshifts enabled by the upcoming CHIME/FRB Outriggers project.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SINGLE-PULSE RADIO OBSERVATIONS OF THE GALACTIC CENTER MAGNETAR PSR J1745–2900

In this paper, we report radio observations of the Galactic Center magnetar PSR J1745–2900 at six epochs between 2014 June and October. These observations were carried out using the new Shanghai Tian Ma Radio Telescope at a frequency of 8.6 GHz. Both the flux density and integrated profile of PSR J1745–2900 show dramatic changes from epoch to epoch, showing that the pulsar was in its “erratic” phase. On MJD 56836, the flux density of this magnetar was about 8.7 mJy, which was 10 times larger than that reported at the time of discovery, enabling a single-pulse analysis. The emission is dominated by narrow “spiky” pulses that follow a log-normal distribution in peak flux density. From 1913 pulses, we detected 53 pulses whose peak flux densities are 10 times greater than that of the integrated profile. They are concentrated in pulse phase at the peaks of the integrated profile. The pulse widths at the 50% level of these bright pulses were between 0.°2 and 0.°9, much narrower than that of the integrated profile (∼12°). The observed pulse widths may be limited by interstellar scattering. No clear correlation was found between the widths and peak flux density of these pulses and no evidence was found for subpulse drifting. Relatively strong spiky pulses are also detected in the other five epochs of observation, showing the same properties as those detected in MJD 56836. These strong spiky pulses cannot be classified as “giant” pulses but are more closely related to normal pulse emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

A variance-based decomposition and global sensitivity index method for uncertainty quantification: Application to retrieved ice cloud properties

This study develops a novel uncertainty quantification (UQ) method for cloud microphysical property retrievals using variance-based decomposition and global sensitivity index. In this UQ framework, empirical orthogonal function (EOF) analysis is applied to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) ground-based observations, which are the inputs for the cloud retrieval studied here. The principal components (PCs) in the EOF expansion are parameterized as random input variables, and hence, the input dimension is greatly reduced (up to a factor of 50), allowing large ensemble of random samplings. The EOF expansion improves the accuracy of the uncertainty estimation by taking into account the cross correlations in the input data profiles. Here, this method enables a probabilistic representation of a retrieval process by adding normally distributed perturbations into PCs of sample means of input data profiles within a time window. Therefore, it effectively facilitates objective validation of climate models against cloud retrievals under a probabilistic framework for rigorous statistical inferences. Moreover, the variance-based global sensitivity index analysis, part of this method, attributes the output uncertainties to each individual source, thus providing directions for improving retrieval algorithms and observation strategies. For demonstration, we apply this method to quantify the uncertainties of the ARM program's baseline cloud retrieval algorithm for an ice cloud case observed at the Southern Great Plains site on 9 March 2000.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A liquid stratification model to predict failure in thermally damaged EBW detonators

In previous work, commercially available downward facing exploding bridgewire detonators (EBWs) were exposed to elevated temperatures. These detonators were then initiated using a firing set which discharged a high amplitude short duration electrical pulse into a thin gold bridgewire. Responses of the detonators were measured using photonic doppler velocimetry (PDV) and high-speed photography. A time delay of 4 μs between EBW initiation and first movement of an output flyer separated operable detonators from inoperable detonators or duds. Here, we propose a simple method to determine detonator operability from the calculated state of the detonator at the time the firing set is initiated. The failure criterion is based on the gap distance between the exploding bridgewire (EBW) and the adjacent initiating explosive within the detonator which is low-density pentaerythritol tetranitrate (PETN) that melts between 413-415 K (140-142 ºC). The gap forms as PETN melts and flows to the bottom of the input pellet. Melting of PETN is modeled thermodynamically as an energy sink using a normal distribution spread over a temperature range between the onset temperature of 413 K and the ending temperature of 415 K. The extent of the melt is determined from the average temperature of the PETN. The PETN liquid is assumed to occupy the interstitial gas volume in the lower part of the input pellet. The vacated volume from the relocated liquid forms the gap between the EBW and the PETN. The remaining sandwiched layer consists of solid PETN particles and gas filling interstitial volume. We predict that a threshold gap between 17-27 μm separates properly functioning detonators from duds.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Revisiting short-term earthquake triggered volcanism

It has been noted for centuries that earthquakes appear to trigger the eruption of volcanoes. For example, analyses of global volcanic and seismic records since 1500 AD have shown that explosive eruptions with Volcanic Explosivity Index (VEI) values ≥2 are preceded within days by nearby major earthquakes (magnitude M8 or larger) about 4 times more often than expected due to coincidence, suggesting that large earthquakes can trigger eruptions. Here we expand the definition of a triggered eruption to include the possibility of M6 or greater earthquakes within 5 days and 800 km of a VEI 2 or greater eruption. Removing pre-1964 records, to ensure complete and accurate catalogs, we find 30 volcanoes that at some point experienced a potentially triggered eruption and define these volcanoes as “sensitive” volcanoes. Within this group of sensitive volcanoes, normalized distributions of volcano-centric factors such as tectonic setting, dominant rock type, and type of volcano are practically indistinguishable from those of sensitive volcanoes in which the time of eruption is randomized. Comparisons of sensitive volcanoes and insensitive volcanoes (i.e., volcanoes that have never experienced a triggered eruption) reveal that sensitive volcanoes are simply more active than insensitive volcanoes: They erupt more frequently, are located solely in subduction zones, and erupt primarily andesites and basaltic-andesites. The potentially triggered eruptions do not show the magnitude-distance relationship expected for seismically induced responses (e.g., hydrologic responses), and eruptions that do occur within days of nearby earthquakes do so within rates expected by random chance. There is, however, a 5–12% increase in the number of explosive eruptions in the 2 months to 2 years following major earthquakes. Finally, we conclude that short-term seismically triggered explosive eruptions occur less frequently than previously inferred, an important conclusion when considering volcanic hazards and for understanding the nature of earthquake-volcano interactions.

58 GEOSCIENCES↗
DOE OSTI2018

Upscaling permeability for three-dimensional fractured porous rocks with the multiple boundary method

Upscaling permeability of grid blocks is crucial for groundwater models. A novel upscaling method for three-dimensional fractured porous rocks is presented. The objective of the study was to compare this method with the commonly used Oda upscaling method and the volume averaging method. First, the multiple boundary method and its computational framework were defined for three-dimensional stochastic fracture networks. Then, the different upscaling methods were compared for a set of rotated fractures, for tortuous fractures, and for two discrete fracture networks. The results computed by the multiple boundary method are comparable with those of the other two methods and fit best the analytical solution for a set of rotated fractures. The errors in flow rate of the equivalent fracture model decrease when using the multiple boundary method. Furthermore, the errors of the equivalent fracture models increase from well-connected fracture networks to poorly connected ones. Finally, the diagonal components of the equivalent permeability tensors tend to follow a normal or log-normal distribution for the well-connected fracture network model with infinite fracture size. By contrast, they exhibit a power-law distribution for the poorly connected fracture network with multiple scale fractures. The study demonstrates the accuracy and the flexibility of the multiple boundary upscaling concept. This makes it attractive for being incorporated into any existing flow-based upscaling procedures, which helps in reducing the uncertainty of groundwater models.

58 GEOSCIENCES↗
DOE OSTI2018

On the Five-Moment Hamburger Maximum Entropy Reconstruction

We consider the Maximum Entropy Reconstruction (MER) as a solution to the five-moment truncated Hamburger moment problem in one dimension. In the case of five monomial moment constraints, the probability density function (PDF) of the MER takes the form of the exponential of a quartic polynomial. This implies a possible bimodal structure in regions of moment space. An analytical model is developed for the MER PDF applicable near a known singular line in a centered, two-component, third- and fourth-order moment (μ{sub 3}, μ{sub 4}) space, consistent with the general problem of five moments. The model consists of the superposition of a perturbed, centered Gaussian PDF and a small-amplitude packet of PDF-density, called the outlying moment packet (OMP), sitting far from the mean. Asymptotic solutions are obtained which predict the shape of the perturbed Gaussian and both the amplitude and position on the real line of the OMP. The asymptotic solutions show that the presence of the OMP gives rise to an MER solution that is singular along a line in (μ{sub 3}, μ{sub 4}) space emanating from, but not including, the point representing a standard normal distribution, or thermodynamic equilibrium. We use this analysis of the OMP to develop a numerical regularization of the MER, creating a procedure we call the Hybrid MER (HMER). Compared with the MER, the HMER is a significant improvement in terms of robustness and efficiency while preserving accuracy in its prediction of other important distribution features, such as higher order moments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Study of the Thermomechanical Performance of FR-4 Laminates During the Reflow Process

The behavior of FR4 laminates for printed circuit boards (PCBs) during a double reflow process and the main factors associated with warpage are discussed. The microstructure, glass transition temperature (T{sub g}), decomposition temperature (T{sub d}), coefficient of thermal expansion (CTE), time to delamination and % water absorption were characterized, and the temperature profiles in the board during its pass through the reflow oven were recorded. Bow and twist measurements were taken on a set of 30 PCBs. Both T{sub d} and T{sub g} were found to be below their nominal values. The CTE is highly anisotropic and vary at different locations, and it is more than three times higher in the through thickness middle section with respect to the bottom and top locations. Temporary temperature gradients of more than 50 degrees between different locations were detected at the start of the reflow step as a result, the bow values were found to be strongly anisotropic, particularly after the first reflow, in which different sides can present bow values up to more than six times higher than others, with maxima values of 0.47 mm. The anisotropy of the CTE appears to affect only slightly the twist values. Compared with the first reflow, the bow and twist values are lower, exhibit less dispersion and are more homogeneous for the second reflow. The histograms of both bow and twist do not seem to follow a normal distribution, possibly as a result of the combined effect of spatial variations and anisotropy of properties as well as the temperature gradients during reflow.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The method of imbedded Lagrangian element to estimate wave power absorption by some submerged devices

A simple approach is described to estimate the wave power absorption potential of submerged devices known to cause wave focusing and flow enhancement. In particular, the presence of a flow-through power take-off (PTO) system, such as low-head turbines, can be accounted for. The wave radiation characteristics of an appropriately selected Lagrangian element (LE) in the fluid domain are first determined. In the limit of a vanishing mass, the LE reduces to a patch of distributed normal dipoles. Here, the hydrodynamic coefficients of this virtual object are then input in a standard equation of motion where the effect of the PTO can be represented, for example, as a dashpot damping term. The process is illustrated for a class of devices recently proposed by Carter and Ertekin (2011), although in a simplified form. Favorable wave power absorption is shown for large ratios of the LE wave radiation coefficient over the LE added mass coefficient. Under optimal conditions, the relative flow reduction from the PTO theoretically lies between 0.50 and 1/√2≈ 0.71, with lower values corresponding to better configurations. Wave power capture widths, the sensitivity of results to PTO damping and sample spectral calculations at a typical site in Hawaiian waters are proposed to further illustrate the versatility of the method.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

Tannic Acid: a Novel Calibrator for Facile and Accurate Mass Measurement of Electrospray Ionization Mass Spectrometry

Accurate mass calibration is beneficial to the identification of the unknown compounds quickly and accurately. The ESI mass spectrum of tannic acid (TA) tends to a normal distribution of the cluster ion peaks in m/z range from 371.0368 to 1739.1169. Based on the interesting result, we reported the use of TA, a natural plant polyphenol, as a novel calibrator for electrospray ionization mass spectrometry (ESI MS), which has the following three advantages, including (1) easy preparation, (2) the calibration range of m/z 200~2000, and (3) the calibration error is around 3.00 ppm in positive ion mode, which is less than the use of sodium formate (SF) and Prod #88323 calibrators. This TA calibrator has great potential for the wide applications in biological, chemical, and pharmacal analysis. .

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Efficient computation of basic sums for random polydispersed composites

The main goal of the paper was to develop algorithms and methods for computation of basic sums, the mathematical objects of great importance in computational materials science having applications to description of the representative volume element (RVE) and to the effective properties of 2D composites. The previously used algorithm had the exponential complexity. We propose a linearly complex algorithm. All the presented algorithms can be easily implemented in modern scientific computing packages, while maintaining both efficient calculations and a high level of abstraction. The proposed approach is applied to derivation of a polynomial approximation of the effective conductivity formula for 2D random material with non-overlapping circular inclusions with normally distributed radii. The obtained formulas are applied to the optimal packing problem of disks on the plane.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Disordered crystals from first principles I: Quantifying the configuration space

This work represents the first chapter of a project on the foundations of first-principle calculations of the electron transport in crystals at finite temperatures. We are interested in the range of temperatures, where most electronic components operate, that is, room temperature and above. The aim is a predictive first-principle formalism that combines ab-initio molecular dynamics and a finite-temperature Kubo-formula for homogeneous thermodynamic phases. The input for this formula is the ergodic dynamical system (Ω,G,dP) defining the thermodynamic crystalline phase, where Ω is the configuration space for the atomic degrees of freedom, G is the space group acting on Ω and dP is the ergodic Gibbs measure relative to the G-action. The present work develops an algorithmic method for quantifying (Ω,G,dP) from first principles. Using the silicon crystal as a working example, we find the Gibbs measure to be extremely well characterized by a multivariate normal distribution, which can be quantified using a small number of parameters. The latter are computed at various temperatures and communicated in the form of a table. Using this table, one can generate large and accurate thermally-disordered atomic configurations to serve, for example, as input for subsequent simulations of the electronic degrees of freedom.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Genetics of osteoporosis

Highlights: • Single-nucleotide polymorphisms (SNPs) associated with osteoporosis were identified. • SNPs mapped close to or within VDR and ESR1 are associated with bone mineral density. • WNT signaling pathway plays a pivotal role in regulating bone mineral density. • Genetic studies will be useful for identification of new therapeutic targets. - Abstract: Osteoporosis is a skeletal disease characterized by low bone mineral density (BMD) and microarchitectural deterioration of bone tissue, which increases susceptibility to fractures. BMD is a complex quantitative trait with normal distribution and seems to be genetically controlled (in 50–90% of the cases), according to studies on twins and families. Over the last 20 years, candidate gene approach and genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) that are associated with low BMD, osteoporosis, and osteoporotic fractures. These SNPs have been mapped close to or within genes including those encoding nuclear receptors and WNT-β-catenin signaling proteins. Understanding the genetics of osteoporosis will help identify novel candidates for diagnostic and therapeutic targets.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Generative learning of densities on manifolds

A generative modeling framework is proposed that combines diffusion models and manifold learning to efficiently sample data densities on manifolds. The approach utilizes Diffusion Maps to uncover possible low-dimensional underlying (latent) spaces in the high-dimensional data (ambient) space. Two approaches for sampling from the latent data density are described. The first is a score-based diffusion model, which is trained to map a standard normal distribution to the latent data distribution using a neural network. The second one involves solving an Itô stochastic differential equation in the latent space. Additional realizations of the data are generated by lifting the samples back to the ambient space using Double Diffusion Maps , a recently introduced technique typically employed in studying dynamical system reduction; here the focus lies in sampling densities rather than system dynamics. The proposed approaches enable sampling high dimensional data densities restricted to low-dimensional, a priori unknown manifolds. The efficacy of the proposed framework is demonstrated through a benchmark problem and a material with multiscale structure.

Double diffusion maps↗
DOE OSTI2023

A new approach to model geomaterials with heterogeneous properties in thermo-hydro-mechanical coupled problems

The main objective of this article is to present a new approach to model coupled thermo-hydro-mechanical problems considering geomaterials with heterogeneous properties. This approach has been implemented in the software CODE_BRIGHT and it provides the possibility of considering geomaterials with a spatially correlated heterogeneous field of porosity, following a normal distribution. This spatial correlation can be isotropic or anisotropic. An important feature of this approach is that material properties such as intrinsic permeability, thermal conductivity, diffusivity, retention curve, elastic modulus or cohesion are defined as a function of porosity and, thus, they become heterogeneous with spatial correlation and, eventually, anisotropic. A validation exercise and other basic numerical examples have been carried out to illustrate the possibilities of the proposed approach. The results, which have been compared with a homogeneous case, show that considering heterogeneous fields can be relevant in different modelling problems, especially coupled thermo-hydro-mechanical problems.

42 ENGINEERING↗