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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Sheaves as a Framework for Understanding and Interpreting Model Fit

As data grows in size and complexity, finding frameworks which aid in interpretation and analysis has become critical. This is particularly true when data comes from complex systems where extensive structure is available, but must be drawn from peripheral sources. In this paper we argue that in such situations, sheaves can provide a natural framework to analyze how well a statistical model fits at the local level (that is, on subsets of related datapoints) vs the global level (on all the data). The sheaf-based approach that we propose is suitably general enough to be useful in a range of applications, from analyzing sensor networks to understanding the feature space of a deep learning model.

Kvinge, Henry J.↗
DOE OSTI2024

Distributed Multi-GPU Community Detection on Exascale Computing Platforms

Community detection is a fundamental operation in graph mining, and by uncovering hidden structures and patterns within complex systems it helps solve fundamental problems pertaining to social networks, such as information diffusion, epidemics, and recommender systems. Scaling graph algorithms for massive networks becomes challenging on modern distributed-memory multi-GPU (Graphics Processing Unit) systems due to limitations such as irregular memory access patterns, load imbalances, higher communication-computation ratios, and cross-platform support. We present a novel algorithm HiPDPL-GPU (distributed parallel Louvain) to address these challenges. We conduct experiments involving different partitioning techniques to achieve optimized performance of HiPDPL-GPU on the two largest supercomputers: Frontier and Summit. Remarkably, HiPDPL-GPU processes a graph with 4.2 billion edges in less than 3 minutes using 1024 GPUs. Qualitatively performance of HiPDPL-GPU is similar or better compared to other state-of-the-art CPU- and GPU-based implementations. While prior GPU implementations have predominantly employed CUDA, our first-of-its-kind implementation for community detection is cross-platform, accommodating both AMD and NVIDIA GPUs.

graph algorithms, high performance comptuing↗
DOE OSTI2025

Adaptive Computing for Scale-Up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

HumoNet: A Framework for Realistic Modeling and Simulation of Human Mobility Network

Understanding, analyzing, and predicting human mobility and dynamics are valuable to solving pressing problems, developing effective plans, and prescribing timely remedies. As a computational approach, realistic human mobility simulations allow us to understand, analyze, and predict complex systems, including human societies. Accurate simulations rely on (1) the model that captures interactions and behaviors of myriad entities in our society and (2) the mapping of model instances to real-world entities. Taking this into account, this paper introduces the Human Mobility Network simulation framework (HumoNet), an integrated patterns of life (POL) simulation framework that leverages real-world data layers including transportation networks, points of interest, populations, popularity, and human trajectories. HumoNet is a data informed model in which agents are equipped with activities, locomotion, and planning capabilities. To simulate realistic kinematic maneuvers of individuals in transportation networks, HumoNet harnesses a microscopic traffic simulator that provides interaction among vehicles and traffic objects. In this paper, we describe the framework, outline our methodologies, and discuss the data processing and challenges of each data layer. Through experiments, we demonstrate that our simulations capture key features of human mobility by comparing them to the literature and real data using standard measures of human mobility (i.e., the radius of gyration, number of locations visited, level of exploration) and metrics scoring (i.e., Jensen-Shannon divergence). We envision that the synthetic data produced by HumoNet will serve as a benchmark for analyzing epidemics, deploying EV charging networks, and validating AI/ML tasks such as location prediction.

Kim, Joon-Seok↗
DOE OSTI2024

Model-Free Control of Indoor Temperatures in Residential Buildings: Convergence Analysis

Model-free control (MFC) has recently been applied in multiple fields, including indoor air temperature regulation in buildings. It is a data-enabled feedback tracking control strategy for complex systems using a simplified representation of the ultra-local approximation model through the unique information of input-output behavior. MFC is a prevailing control strategy for systems with unknown or poorly known system dynamic models. Thus, it is a relatively simple, but efficient, trajectory tracking controller. In this paper, we investigate the convergence rate of MFC when applied to controlling indoor temperatures in residential buildings subject to outdoor weather disturbances. Numerical results show that MFC is quite robust to external disturbances, and its rate of convergence is almost one, i.e., it converges Q-sublinearly (slower than linearly).

Wu, Tumin↗
DOE OSTI2021

Exploring PV Circularity by Modeling Socio-Technical Dynamics of Modules’ End-of-Life Management

The circular economy (CE) tackles environmental and resource scarcity issues by maximizing value retention in the economy. The concept implies design strategies such as reducing the use of materials or improving products’ durability and end-of-life (EOL) strategies, for example, reusing products and components and recycling materials. With an estimated 80 million tons of global cumulative EOL photovoltaic (PV) modules, applying CE principles to the PV industry could alleviate resource scarcity issues while also providing economic benefits. However, transitioning to a CE may imply changes in organizations and consumer behaviors. In this context, assessment of CE strategies may require accounting for behavioral change, a requirement that methods from complex system science such as agent-based modeling meet. Thus, this paper uses an agent-based modeling (ABM) approach to study circularity in the photovoltaics supply chain. Four types of agents are represented in the ABM: PV owners, installers, recyclers, and manufacturers. Moreover, five possible EOL options – including three CE strategies – are modeled. Departing from traditional techno-economic analysis, the model includes techno-economic factors as well as social factors to model EOL management decisions. Results show that each dollar decrease in the recycling fees improves the recycling rate by roughly 1.1%. However, excluding social factors underestimates the effect that lower recycling prices have on material circularity.

agent-based modeling↗
DOE OSTI2021

Leveraging Structured Biological Knowledge for Counterfactual Inference: A Case Study of Viral Pathogenesis

Counterfactual inference is a useful tool for comparing outcomes of interventions on complex systems. It requires us to represent the system in form of a structural causal model, complete with a causal diagram, probabilistic assumptions on exogenous variables, and functional assignments. Specifying such models can be extremely difficult in practice. The process requires substantial domain expertise, and does not scale easily to large systems, multiple systems, or novel system modifications. At the same time, many application domains, such as molecular biology, are rich in structured causal knowledge that is qualitative in nature. This manuscript proposes a general approach for querying a causal knowledge graph with a causal question and converting the qualitative result into a quantitative structural causal model that can learn from data to answer the question. Here, we demonstrate the feasibility, accuracy and versatility of this approach using two case studies in systems biology. The first demonstrates the appropriateness of the underlying assumptions and the accuracy of the results. The second demonstrates the versatility of the approach by querying a knowledge base for the molecular determinants of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced cytokine storm and performing counterfactual inference to predict the causal effect of medical countermeasures for severely ill COVID-19 patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Experimental Safe Extremum Seeking for Accelerators

Here, we demonstrate the recent designs of safe extremum seeking (Safe ES) on the 1-km-long charged particle accelerator at the Los Alamos Neutron Science Center (LANSCE). Safe ES is a modification of extremum seeking (ES) which, in addition to minimizing an analytically unknown cost, also employs a safety filter based on an analytically unknown control barrier function (CBF) safety metric. Tuning is necessitated by accelerators being large complex systems, with many drifting parameters due to thermal effects and degradation. At the same time, safe operation (the maintenance of state constraints) is crucial, as damage brings astronomical costs, both financially and in operation downtime. Our measured (but analytically unknown) safety metric is the beam current. We perform multivariable Safe ES on three accelerator applications, in which we adapt 4, 6, and 3 magnet strength parameters, respectively. Two of the three applications are for validated simulation models of beamlines at LANSCE: the first for the proton radiography (pRad) beamline of 800-MeV protons for spot size tuning; the second on a high-performance code, HPSim, for tuning the low-energy beam transport (LEBT) region that contains a beam of 750-keV protons. The third is an experimental tuning of the steering magnets in the LEBT at LANSCE.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

A Double-Wiebe Function for Reactivity Controlled Compression Ignition Combustion Using Reformate Diesel

Abstract Reactivity controlled compression ignition (RCCI) combustion has previously been proposed as a method to achieve high fuel conversion efficiency and reduce engine emissions. A single-fuel RCCI combustion strategy can have decreased fuel system complexity by using a reformate fuel for port fuel injection and the parent fuel (diesel) for direct injection. This paper presents a one-dimensional computational model of a compression ignition engine with single-fuel RCCI. A Wiebe function is used to predict the combustion process by representing the mass fraction burned (MFB) on a crank angle resolved basis. One single-Wiebe function (SWF) and two double-Wiebe functions(DWFs) were fitted to experimentally derive MFB data using the least-square method. The fitted results were compared with MFBs calculated from experimental data to verify the accuracy. The SWF did not fully capture the MFB curve with high fidelity while the detailed DWF captured the MFB curve within a root mean square error of 1.4%. The reduced double-Wiebe function (RDWF) also resulted in a predicted combustion profile with similar accuracy. Hence, the RDWF was used in a GT-power thermodynamic study to understand the effects of the low-temperature heat release (LTHR) fraction and combustion phasing on combustion characteristics. At optimum phasing of 5–10 crank angle degree after the top dead center, increasing the LTHR fraction from 20% to 60% resulted in the fuel conversion efficiency increasing from 39.5% to 41.1%, thus suggesting that the reformate fuel-based RCCI strategy is viable to unlock improved combustion performance.

Energy & Fuels↗
DOE OSTI2022

In situ temperature measurements in sooting methane/air flames using synchrotron x-ray fluorescence of seeded krypton atoms

Synchrotron x-ray fluorescence has been used to measure temperatures in optically dense gases where traditional methods would fail. These data provide a benchmark for stringent tests of computational fluid dynamics models for complex systems where physical and chemical processes are intimately linked. The experiments measured krypton number densities in a sooting, atmospheric pressure, nonpremixed coflow flame that is widely used in combustion research. The experiments not only form targets for the models, but the simulations also identify potential sources of uncertainties in the measurements, allowing for future improvements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A tandem radiative/evaporative cooler for weather-insensitive and high-performance daytime passive cooling

Radiative cooling and evaporative cooling with low carbon footprint are regarded as promising passive cooling strategies. However, the intrinsic limits of continuous water supply with complex systems for evaporative cooling, and restricted cooling power as well as the strict requirement of weather conditions for radiative cooling, hinder the scale of their practical applications. Here, we propose a tandem passive cooler composed of bilayer polymer that enables dual-functional passive cooling of radiation and evaporation. Specifically, the high reflectivity to sunlight and mid-infrared emissivity of this polymer film allows excellent radiative cooling performance, and its good atmospheric water harvesting property of underlayer ensures self-supply of water and high evaporative cooling power. Consequently, this tandem passive cooler overcomes the fundamental difficulties of radiative cooling and evaporative cooling and shows the applicability under various conditions of weather/climate. It is expected that this design can expand the practical application domain of passive cooling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Toward perturbation theory methods on a quantum computer

Perturbation theory, used in a wide range of fields, is a powerful tool for approximate solutions to complex problems, starting from the exact solution of a related, simpler problem. Advances in quantum computing, especially over the past several years, provide opportunities for alternatives to classical methods. Here, we present a general quantum circuit estimating both the energy and eigenstates corrections that is far superior to the classical version when estimating second-order energy corrections. We demonstrate our approach as applied to the two-site extended Hubbard model. In addition to numerical simulations based on qiskit, results on IBM’s quantum hardware are also presented. Our work offers a general approach to studying complex systems with quantum devices, with no training or optimization process needed to obtain the perturbative terms, which can be generalized to other Hamiltonian systems both in chemistry and physics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Interleaved dual-species arrays of single atoms using a passive optical element and one trapping laser

We demonstrate trapping of individual rubidium (Rb) and cesium (Cs) atoms in an interleaved array of bright tweezers and dark bottle-beam traps, using a microfabricated optical element illuminated by a single-laser beam and a 4f system with spatial filtering. Our approach exploits the opposite-sign dynamic polarizabilities of Rb and Cs, ensuring that each species is exclusively trapped in either bright or dark sites. The passive optical mask creates optimal trap depths for both species using three transmittance levels while minimizing the optical phase difference, implemented using a variable-thickness absorbing layer of amorphous germanium. This trapping architecture achieves atom loading rates close to 50% while reducing system complexity compared to conventional methods using active optoelectronic components and/or multiple-laser wavelengths.

Fang, Chengyu [Univ. of Wisconsin, Madison, WI (Un↗
DOE OSTI2026

Universal progression of structure and dynamics in colloidal nanocrystal gels during salt-accelerated aging

Controlling the structure and function of colloidal gels requires a detailed understanding of how the various components govern network formation and aging. In particular, molecular additives like salts are widely used to tune interparticle interactions, yet their influence on gelation pathways in complex systems such as colloidal nanocrystal gels remains inadequately understood. Here, we investigate how noncoordinating salts modulate the evolution of gels formed using chemically linked tin-doped indium oxide nanocrystals. Through combined structural, dynamic, and kinetic analyses, we demonstrate that increasing salt concentration accelerates gelation. When rescaled by salt-dependent characteristic times, the evolution collapses onto universal trajectories, revealing a time-salt superposition principle. The universality extends across length scales, suggesting a consistent salt-dependent mechanism that controls both local structuring and macroscopic network formation. This observed salt modulation of structure and dynamics provides a predictive basis for controlling the kinetics of nonequilibrium nanocrystal gel assembly, enhancing the rational design of functional nanomaterials with tunable properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Femtosecond symmetry breaking and coherent relaxation of methane cations via x-ray spectroscopy

Understanding the relaxation pathways of photoexcited molecules is essential to gain atomistic-level insight into photochemistry. Here, we performed a time-resolved study of ultrafast molecular symmetry breaking through geometric relaxation (Jahn-Teller distortion) on the methane cation. Attosecond transient absorption spectroscopy with soft x-rays at the carbon K-edge revealed that the distortion occurred within 10 ± 2 femtoseconds after few-femtosecond strong-field ionization of methane. The distortion activated coherent oscillations in the asymmetric scissoring vibrational mode of the symmetry-broken cation, which were detected in the x-ray signal. These oscillations were damped within 58 ± 13 femtoseconds because vibrational coherence was lost with the energy redistributing into lower-frequency vibrational modes. This study completely reconstructs the molecular relaxation dynamics of this prototypical example and opens avenues for exploring complex systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Scalable Bayesian Physics-Informed Kolmogorov-Arnold Networks

Uncertainty quantification (UQ) plays a pivotal role in scientific machine learning, especially when surrogate models are used to approximate complex systems. Although multilayer perceptions (MLPs) are commonly employed as surrogates, they often suffer from overfitting due to their large number of parameters. Kolmogorov-Arnold networks (KANs) offer an alternative solution with fewer parameters. However, gradient-based inference methods, such as Hamiltonian Monte Carlo (HMC), may result in computational inefficiency when applied to KANs, especially for large-scale datasets, due to the high cost of back-propagation. To address these challenges, we propose a novel approach, combining the dropout Tikhonov ensemble Kalman inversion (DTEKI) with Chebyshev KANs. This gradient-free method effectively mitigates overfitting and enhances numerical stability. In addition, we incorporate the active subspace method to reduce the parameter-space dimensionality, allowing us to improve the accuracy of predictions and obtain more reliable uncertainty estimates. Extensive experiments demonstrate the efficacy of our approach in various test cases, including scenarios with large datasets and high noise levels. Our results show that the new method achieves comparable or better accuracy, much higher efficiency as well as stability compared to HMC, in addition to scalability. Moreover, by leveraging the low-dimensional parameter subspace, our method preserves prediction accuracy while substantially reducing further the computational cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Towards Superior Software Portability with SHAD and HPX C++ Libraries

As hardware architectures and software stacks complexity grows, development productivity, performance and software portability, quickly evolve from desirable features to actual needs. SHAD, the Scalable High-performance Algorithms and Data-structures C++ library is designed to mitigate these issues: it provides general purpose building blocks as well as high-level custom utilities, and offers a shared-memory programming abstraction which facilitates the programming of complex systems, scaling up to High Performance Computing clusters. SHAD’s portability is achieved through an abstract runtime interface, which decouples the upper layers of the library and hides the low level details of the underlying architecture. This layer enables SHAD to interface with different runtime/threading systems, e.g. Intel TBB and Global Memory and Threading (GMT). However, current backends targeting distributed systems, rely on a centralized controller which may possibly limit scalability up to hundreds of nodes and creates a network hot spot due to all to one communication for synchronization, and possibly resulting in degraded performance at high process counts. In this research, we explore HPX, the C++ standard library for parallelism and concurrency, as an additional backend in support of the SHAD library, and present the methodologies in support of local and remote task executions in SHAD with respect to HPX. Finally, we evaluate the proposed system by comparing against existing backends of SHAD and analyzing their performance on C++ Standard Template Library algorithms.

Wu, Nanmiao↗
DOE OSTI2024

Aqueous Titania Interfaces

Water–metal oxide interfaces are central to many phenomena and applications, ranging from material corrosion and dissolution to photoelectrochemistry and bioengineering. In particular, the discovery of photocatalytic water splitting on TiO 2 has motivated intensive studies of water-TiO 2 interfaces for decades. So far, a broad understanding of the interaction of water vapor with several TiO 2 surfaces has been obtained. However, much less is known about liquid water–TiO 2 interfaces, which are more relevant to many practical applications. Probing these complex systems at the molecular level is experimentally challenging and is sometimes possible only through computational studies. This review summarizes recent advances in the atomistic understanding, mostly through computational simulations, of the structure and dynamics of interfacial water on TiO 2 surfaces. The main focus is on the nature, molecular or dissociated, of water in direct contact with low-index defect-free crystalline surfaces. The hydroxyls resulting from water dissociation are essential in the photooxidation of water and critically affect the surface chemistry of TiO 2.

density functional theory↗