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At least 181 records · Page 10

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DOE OSTI2024

Physics-informed neural networks for heterogeneous poroelastic media

This study presents a novel physics-informed neural network (PINN) framework for modeling poroelasticity in heterogeneous media with material interfaces. The approach introduces a composite neural network (CoNN) where separate neural networks predict displacement and pressure variables for each material. While sharing identical activation functions, these networks are independently trained for all other parameters. To address challenges posed by heterogeneous material interfaces, the CoNN is integrated with the Interface-PINNs (I-PINNs) framework (Sarma et al., Comput. Methods Appl. Mech. Eng. 429: 117135, 2024), allowing different activation functions across material interfaces. Further, this ensures accurate approximation of discontinuous solution fields and gradients. Performance and accuracy of this combined architecture were evaluated against the conventional PINNs approach, a single neural network (SNN) architecture, and the eXtended PINNs (XPINNs) framework through two one-dimensional benchmark examples with discontinuous material properties. The results show that the proposed CoNN with I-PINNs architecture achieves an RMSE that is two orders of magnitude better than the conventional PINNs approach and is at least 40 times faster than the SNN framework. Compared to XPINNs, the proposed method achieves an RMSE at least one order of magnitude better and is 40% faster.

42 ENGINEERING↗

DOE OSTI2026

Block encoding of the three-dimensional heterogeneous Poisson equation with application to fracture flow

Quantum linear system (QLS) algorithms offer the potential to solve large-scale linear systems exponentially faster than classical methods. However, applying QLS algorithms to real-world problems remains challenging due to issues such as state preparation, data loading, and efficient information extraction. In this work, we study the feasibility of applying QLS algorithms to solve discretized three-dimensional (3D) heterogeneous Poisson equations, with specific examples relating to groundwater flow through geologic fracture networks. We explicitly construct a block encoding for the 3D heterogeneous Poisson matrix by leveraging the sparse local structure of the discretized operator. While classical solvers benefit from preconditioning, we show that block encoding the system matrix and preconditioner separately does not improve the effective condition number that dominates the QLS run-time. This differs from classical approaches where the preconditioner and the system matrix can often be implemented independently. Nevertheless, due to the structure of the problem in three dimensions, the quantum algorithm achieves a run-time of 𝑂⁡(𝑁 2/3 polylog 𝑁 ⋅log (1/𝜖)), outperforming the best classical methods (with run times of 𝑂⁡(𝑁⁢log 𝑁 ⋅log (1/𝜖))) and offering exponential memory savings. These results highlight both the promise and limitations of QLS algorithms for practical scientific computing, and point to effective condition-number reduction as a key barrier in achieving quantum advantages.

58 GEOSCIENCES↗

DOE OSTI2024

Heterogeneous Cluster Energetics and Nonlinear Thermodynamic Response in Supercritical Fluids

Microstructural heterogeneities arising from molecular clusters directly affect the nonlinear thermodynamic properties of supercritical fluids. We present a physical model to elucidate the relation between energy exchange and heterogeneous cluster dynamics during the transition from liquidlike to gaslike conditions. By analyzing molecular-dynamics data and employing physical principles, the model considers contributions from three key processes, namely, changing cluster density, cluster separation, and transfer of molecules between clusters. We show that the proposed model is consistent with the energetics at subcritical conditions and can be used to explain the nonlinear behavior of thermodynamic response functions, including the peak in the isobaric heat capacity.

42 ENGINEERING↗

DOE OSTI2024

CHARM-SYCL & IRIS: A Tool Chain for Performance Portability on Extremely Heterogeneous Systems

Performance portability is becoming crucial as high-performance computing systems become increasingly heterogeneous. We have many options for CPUs and accelerators (e.g., GPUs) but also for non-Von Neumann architectures such as field-programmable gate arrays. This paper presents the CHARM-SYCL unified programming environment for multiple accelerator types as a performance-portable programming environment. It uses the IRIS library developed at Oak Ridge National Laboratory as the back end accelerator runtime. IRIS has a high-performance scheduler to distribute tasks across accelerators. This design allows us to run an application from the same source on multiple systems with multiple configurations. We provide three types of portability with CHARM-SYCL: Portable Workflow, Compiler and Runtime Portability, and Application and Performance Portability. We implement a Monte Carlo simulation benchmark code on the CHARM-SYCL execution environment and demonstrate that our programming environment can accommodate extremely heterogeneous systems.

Fujita, Norihisa↗

DOE OSTI2026

Optimal Client Sampling in Federated Learning with Client-level Heterogeneous Differential Privacy

Federated Learning with client-level differential privacy (DP) provides a promising framework for collaboratively training models while rigorously protecting clients’ privacy. However, classic approaches like DP-FedAvg struggle when clients have heterogeneous privacy requirements, as they must uniformly enforce the strictest privacy level across all clients, leading to excessive DP noise and significant degradation in model utility. Existing methods to improve the model utility in such heterogeneous privacy settings often assume a trusted server and are largely heuristic, resulting in suboptimal performance and lacking strong theoretical foundations. Here, in this work, we address these challenges under a practical attack model where both clients and the server are honest-but-curious. We propose GDPFed, which partitions clients into groups based on their privacy budgets and achieves client-level DP within each group to reduce the privacy budget waste and hence improve the model utility. Based on the privacy and convergence analysis of GDPFed, we find that the magnitude of DP noise depends on both model dimensionality and the per-group client sampling ratios. To further improve the performance of GDPFed, we introduce GDPFed+, which integrates model sparsification to eliminate unnecessary noise and optimizes per-group client sampling ratios to minimize convergence error. Extensive empirical evaluations on multiple benchmark datasets demonstrate the effectiveness of GDPFed+, showing substantial performance gains compared with state-of-the-art methods.

Xu, Jiahao [Univ. of Nevada, Reno, NV (United Stat↗

DOE OSTI2026

Risk-Aware Measurement Synchronization and Recovery for DSSE With Heterogeneous Data Sources

Power distribution systems are increasingly integrating heterogeneous sensors with varying data reporting rates and types, which pose challenges to achieving observability at the desired temporal resolution of distribution system state estimation (DSSE). Multisensor failures caused by extreme events exacerbate these issues, introducing substantial uncertainties into DSSE. This article proposes a novel solution to these challenges by ensuring high-resolution system observability despite heterogeneous data sources and multisensor failures. First, a deep learning architecture combining long short-term memory (LSTM) and graph convolutional network (GCN) is employed to synchronize meters with different reporting rates, aiming to achieve system observability. A random-walk-model-based approach is introduced to generate pseudo-measurements while properly characterizing their uncertainties under multisensor failures. Finally, a disaster-risk-informed observability metric (RiOM) is defined to quantify the uncertainty associated with state estimation results. The proposed framework offers deeper insights into the system observability on the fly compared with conventional analysis. The effectiveness of the framework is demonstrated on an IEEE standard test case and a large-scale real-world distribution feeder in mid-Minnesota in the U.S.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Orchard: Heterogeneous Parallelism and Fine-grained Fusion for Complex Tree Traversals

Many applications are designed to perform traversals ontree-likedata structures. Fusing and parallelizing these traversals enhance the performance of applications. Fusing multiple traversals improves the locality of the application. The runtime of an application can be significantly reduced by extracting parallelism and utilizing multi-threading. Prior frameworks have tried to fuse and parallelize tree traversals using coarse-grained approaches, leading to missed fine-grained opportunities for improving performance. Other frameworks have successfully supported fine-grained fusion on heterogeneous tree types but fall short regarding parallelization. We introduce a new frameworkOrchardbuilt on top ofGrafter.Orchard’s novelty lies in allowing the programmer to transform tree traversal applications by automatically applyingfine-grainedfusion and extractingheterogeneousparallelism.Orchardallows the programmer to write general tree traversal applications in a simple and elegant embedded Domain-Specific Language (eDSL). We show that the combination of fine-grained fusion and heterogeneous parallelism performs better than each alone when the conditions are met.

Computer Science↗

DOE OSTI2024

P38 heterogeneous multi-tiled system with support for message queues (MoSAIC) v0.1

The proposed system is written in the hardware description language (HDL) verilog targeting an FPGA board. It is intended as a testbed to explore architecture tradeoffs in multi-tiled heterogeneous architectures. Although we target FPGAs, the system can be implemented as a monolithic SoC or a package comprised of many chiplets that are interconnected in the same package using a NoC. The proposed NoC is lightweight and follows an axi-lite interface. The endpoints of the NoC are a heterogeneous mix of "tiles" as endpoints that are general purpose processors, fixed function accelerators, and programmable accelerators. We assume that the network interfaces for the NoC endpoints are all addressable in a global name-space in that they represent an address range (for memory addresses) or a range of unique identifiers that are associated with each individual tile. This makes the functionality abstract from the standpoint of the NoC design details. Message queues offer a direct inter-processor interface between peer general purpose cores and diverse accelerators that comprise an SoC. Although they share the same NoC infrastructure for inter-tile communication within an SoC or SiP, the hardware message queues bypass the memory hierarchy and thus do not pollute the memory state or invoke the cache coherence mechanism.

Gonzalez, LouisaPatricia↗

DOE OSTI2025

Forest Breeze–Cold Pool Interactions Drive Convective Organization over Heterogeneous Vegetation

Heterogeneous landscapes can influence the development of convection through the generation of thermally driven mesoscale circulations. To assess the impacts of these circulations and their interaction with sea breezes, we simulated convection in an idealized coastal environment using the Regional Atmospheric Modeling System (RAMS). We compared simulations with striped patterns of surface vegetation to those of uniform vegetation to identify the importance of vegetation heterogeneity in impacting convective development. Under dry soil conditions representative of those during the Tracking Aerosol Convection Interactions Experiment (TRACER) and Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE) campaigns in June 2022, we found that these vegetation-induced circulations, referred to in the literature as “forest breezes,” are more important than the sea breeze in determining the location of convection initiation. Convection and precipitation are also found to be favored over forests and suppressed over pasture and suburban landscapes as a result of greater surface sensible heat flux over the forest. Our findings also indicate that forest breezes are important for initiating convection along the boundaries of the forest, but that cold pools may play a key role in propagating the forest breezes toward the center of the forest stripe. In our simulations, the collisions of these breezes in the center of the forest stripe lead to uplift and strong convection there; however, a different width of the forest stripe would alter when the forest breezes collide or whether they collide at all. The presence of these cold pools may therefore impact the “ideal stripe width,” the width of each vegetation stripe which maximizes domain-wide precipitation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Impact of Pressure-Dependent Interfacial Tension and Contact Angle on Capillary Heterogeneity Trapping of CO2 in Storage Aquifers

Summary Carbon dioxide (CO2) capillary trapping increases the total amount of CO2 that can be effectively immobilized in storage aquifers. This trapping, manifesting itself as accumulated CO2 columns at a continuum scale, is because of capillary threshold effects that occur below low-permeability barriers. Considering that capillary pressure is dictated by heterogeneous pore throat size, the trapped CO2 column height and associated CO2 saturation will vary spatially within a storage aquifer. This variation will be influenced by two pressure-dependent interfacial parameters—CO2/brine interfacial tension (IFT) and CO2/brine/rock contact angle. Our objective is to understand how the pressure dependence of these two parameters affects the heterogeneity of capillary trapped CO2 at a continuum scale. Our conceptual model is a 1D two-zone system with the upper zone being a flow barrier (low permeability) and the lower zone being a flow path (high permeability). The inputs to this model include microfacies-dependent capillary pressure vs. saturation curves and permeability values. The input capillary pressure curves were collected in the literature that represents carbonate microfacies (e.g., dolograinstone) in a prevalent formation in the Permian Basin. We then used the Leverett j-function to scale the capillary pressure curve for the two zones that are assigned with the same or different microfacies. During scaling, we considered the influence of pressure on both the IFT and contact angle of CO2/brine/dolomite systems. We varied the zone permeability contrast ratio from 2 to 50. We then assumed capillary gravity equilibriums and calculated the CO2 saturation buildup corresponding to various trapped CO2 column heights. The CO2 saturation buildup is defined as the CO2 saturation in the lower layer minus that in the upper one. We found that the saturation buildup can be doubled when varying pressure in a storage aquifer, after considering pressure-dependent IFT and contact angles. Thus, assuming these two parameters to be constant across such aquifers would cause large errors in the quantification of capillary trapping of CO2. The whole study demonstrates the importance of considering pressure-dependent interfacial properties in predicting the vertical distribution of capillary trapped CO2. It has important implications in developing a better understanding of leakage risks and consequent storage safety.

Engineering↗

DOE OSTI2025

Heterogeneous Computing

To leverage the increasing heterogeneity in modern computing resources, Geant4 incorporates advanced software tools and a task-based framework (G4Tasking) that enables efficient parallelism at event, sub-event, and track levels. Ongoing R&D efforts focus on integrating GPUs into high-energy physics (HEP) simulations, including optical photon simulation with Opticks/NVIDIA OptiX, offloading electromagnetic particle transport using G4HepEM/AdePT and Celeritas, and employing advanced surface-based geometry models such as VecGeom2.0 and ORANGE. As Geant4 continues evolving toward high-performance computing (HPC) and heterogeneous architectures, it remains a key tool for large-scale simulations in HEP and beyond.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Ion Traps and Packaging for Heterogenous Integration - Chimera

Microfabricated surface ion traps and silicon-based photonics are critical technologies for scaling quantum systems. Current ion trap architectures face scalability and integration challenges due to limitations in optical access, fabrication techniques, and material compatibility. State-of-the-art quantum computers and atomic clocks are investigating monolithic integration, which necessitates custom traps for each ion species and has not overcome the integration hurdles presented by merging these technologies. The Chimera (Ion Traps and Packaging for Heterogeneous Integration) project proposes a novel approach utilizing heterogeneous integration (HI) of ion traps and photonic circuits. This separation of components allows for flexibility in ion trap design and reduces fabrication compromises. The Chimera project specifically designed an ion trap to interface vertically with a separately fabricated waveguide chip and demonstrates the first steps to integrating them at the packaging level. The ion trap features a large area of removed silicon, allowing the photonics chip outputs closer to the ion trap, improving alignment and packaging processes. The alignment must be accurate to < 1 µm to ensure that the light from the waveguide can overlap with the trapping region. This fine alignment must also be maintained through an ultra-high vacuum bake, a critical step in preparing an ion trap experiment. By combining separate chips, we demonstrate a new path for scaling trapped ion technology that is less reliant on monolithic integration. We successfully fabricated a trap with a large area of oxide removed, resulting in a region thinned to about 40 µm, a key milestone toward successful integration.

42 ENGINEERING↗

DOE OSTI2026

Heterogeneous Multi-Domain Dataset Synthesis to Facilitate Privacy and Risk Assessments in Smart City IoT

The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.

IoT↗

NASA NTRS1973

Nonlinear problems of the theory of heterogeneous slightly curved shells

An account if given of the variational method of the solution of physically and geometrically nonlinear problems of the theory of heterogeneous slightly curved shells. Examined are the bending and supercritical behavior of plates and conical and spherical cupolas of variable thickness in a temperature field, taking into account the dependence of the elastic parameters on temperature. The bending, stability in general and load-bearing capacity of flexible isotropic elastic-plastic shells with different criteria of plasticity, taking into account compressibility and hardening. The effect of the plastic heterogeneity caused by heat treatment, surface work hardening and irradiation by fast neutron flux is investigated. Some problems of the dynamic behavior of flexible shells are solved. Calculations are performed in high approximations. Considerable attention is given to the construction of a machine algorithm and to the checking of the convergence of iterative processes.

Kantor, B. Y.↗

NASA NTRS1978

Application of normal mode theory to seismic source and structure problems: Seismic investigations of upper mantle lateral heterogeneity

The theory of the normal modes of the earth is investigated and used to build synthetic seismograms in order to solve source and structural problems. A study is made of the physical properties of spheroidal modes leading to a rational classification. Two problems addressed are the observability of deep isotropic seismic sources and the investigation of the physical properties of the earth in the neighborhood of the Core-Mantle boundary, using SH waves diffracted at the core's surface. Data sets of seismic body and surface waves are used in a search for possible deep lateral heterogeneities in the mantle. In both cases, it is found that seismic data do not require structural differences between oceans and continents to extend deeper than 250 km. In general, differences between oceans and continents are found to be on the same order of magnitude as the intrinsic lateral heterogeneity in the oceanic plate brought about by the aging of the oceanic lithosphere.

Okal, E. A.↗

NASA NTRS1979

Heterogeneous atmospheric reactions - Sulfuric acid aerosols as tropospheric sinks

The reaction probabilities of various atmospheric species incident on a bulk sulfuric acid surface are measured in order to determine the role of sulfuric acid aerosols as pollutant sinks. Reaction products and unreacted starting materials leaving a Knudsen cell flow reactor after collision at 300 K with a H2SO4 surface or a soot surface were detected by mass spectrometry. Significant collision reaction probabilities are observed on a H2SO4 surface for H2O2, HNO3, HO2NO2, ClONO2, N2O5, H2O and NH3, and on soot for NH3. Estimates of the contribution of heterogeneous reactions to pollutant removal under atmospheric conditions indicate that while aerosol removal in the stratosphere is insignificant (loss rate constants approximately 10 to the -10th/sec), heterogeneous reactions may be the dominant loss process for several tropospheric species (loss rate constant approximately 10 to the -5th/sec, comparable to photolysis rate constants).

Baldwin, A. C.↗

NASA NTRS1980

The relation of mantle heterogeneity to the bulk composition and origin of the earth

The heterogeneity of the mantle can be viewed in the context of models for accretion of the terrestrial planets from the solar nebula. Oxygen isotope ratios and mineralogy indicate the existence of hot planetesimals of diverse compositions. Assuming that nebular condensates range from a reduced state near the sun to an oxidized state near Jupiter, a new model is proposed for heterogeneous accretion of the earth beginning with hot, reduced condensates and ending with cool, oxidized condensates. The Ganapathy-Anders cosmochemical model for the bulk composition of the earth was tested by summing measured compositions for the three outer zones and likely compositions for the inner zones. Revisions are suggested, including reduction of the content of the early condensate from that suggested by taking the U concentration as 30 ng/g, as suggested by the naive interpretation of the heat flow.

Smith, J. V.↗

NASA NTRS1981

Heterogeneous decomposition of silane in a fixed bed reactor

Heterogeneous decomposition of silane in a fluidized bed offers an attractive route for the low-cost production of silicon for photovoltaic application. To obtain design data for a fluid bed silane pyrolysis reactor, deposition experiments were conducted in a small-scale fixed bed apparatus. Data on the decomposition mode, plating rate, and deposition morphology were obtained in the temperature range 600 900 C. Conditions favorable for heterogenous decomposition with good deposition morphology were identified. The kinetic rate data showed the reaction to be first order with an activation energy of 38.8 kcal/mole, which agrees well with work done by others. The results are promising for the development of an economically attractive fluid bed process.

Iya, S. K.↗