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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Application of Banking Scoring and Rating for Coherent Risk Measures in Electricity Systems ABSCORES

This project developed a framework for asset and system risk management that can be incorporated into current electricity system operations to improve economic efficiency and establish an Electric Assets Risk Bureau. We leveraged scoring and ratings from banking and financial institutions alongside current optimization methods in dispatching power systems to help system operators and electricity markets schedule resources. This approach is based on the observation that there are major discrepancies between the power scheduled by a system operator and the actual power generated/consumed. These discrepancies—exacerbated by unplanned contingencies (e.g., natural disasters)—are caused by multiple factors, including the different financial, environmental and risk preferences of power producers, consumers, and aggregators. We developed a framework that counteracts two failures in electricity system operations: imperfect information and missing markets for products. The technical approach included five tasks. Tasks 1 and 2 supported the development of risk scores at the asset level with historical data collected for this project. Tasks 3, 4, and 5 incorporated scoring into decision-making at the system level. The proposed effort achieved PERFORM's Program Objectives because the proposed outputs and algorithms do not exist in the electricity industry and are an innovative approach to managing risk. Since the acknowledged need to better assess and act upon risk profiles for grid assets has not been met by the industry, this project will also impact ARPA-E's Mission Areas, including improving energy efficiency and giving the U.S. a technological lead in advanced energy technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Effects of Microbial-Mineral Interactions on Organic Carbon Stabilization in a Ponderosa Pine Root Zone: A Micro-Scale Approach

Soil microbial communities affect the formation of micro-scale mineral-associated organic matter (MAOM) where complex processes, including adhesion, aggregate formation, microbial mineral weathering and soil organic matter stabilization occur in a narrow zone of large biogeochemical gradients. Here we designed a field study to examine carbon stabilization mechanisms by using in-growth mesh bags containing biotite that were placed in a ponderosa pine root zone for 6 months and compared to the surrounding bulk soil. We sought to determine the composition of the microbial community in the mesh bags compared to the surrounding soils, analyze the direct interactions between microbes and biotite, and finally identify the nature of the newly formed MAOM within the mesh-bags. Our results revealed that minerals in the mesh bags were colonized by a microbial community that produced organic matter in situ. The 16S rRNA gene sequencing and ITS2 region characterization showed phylogenetic similarity between the mesh bag and bulk soil archaea/bacteria and fungi microbiomes, with significant differences in alpha- and beta-diversity and species abundances. Organic matter pools in the mesh bags, analyzed by Fourier transform ion cyclotron resonance mass spectrometry, contained protein- (peptides) and lipid-like compounds while the bulk soil OM was comprised of lignin-like and carboxyl-rich alicyclic molecules. These results support that the newly formed biotite associated organic compounds have a microbial signature in the mesh bags. High-resolution electron microscopy documented strongly adhered organic compounds to biotite surfaces, formation of microaggregates, elemental uptake at the microbe (organic matter)-mineral interface, and distortion of biotite layers. Overall, this study shows the direct and indirect involvement of soil microbial communities from the root zone of ponderosa pine in the formation of MAOM, soil organic carbon stabilization, microaggregation, and mineral weathering at micro- and nano-scales.

58 GEOSCIENCES↗
DOE OSTI2023

Label Assist: Personalized Travel Models for Longitudinal Data Collection

Understanding travel behavior is crucial to transportation decarbonization. OpenPATH is an open-source mobility platform which collects and analyzes human travel behavior at the individual level. The mobile application passively senses trips and prompts users to label them. However, users find the labeling process burdensome; less than half the trips are typically labeled, making much of the data unusable in aggregate analyses of mobility patterns. Prior work has addressed the response fatigue challenge through automated mode inference using sensor data, but sensors cannot capture all aspects of travel behavior. We explore an alternative approach in which we leverage prior user input to predict travel choices in novel trips. We first explore trip clustering methods and develop a novel two-step pipeline using DBSCAN and SVMs to extract realistic geospatial clusters. We then propose two strategies to predict trip labels: (i) clustering trips and extrapolating labels for similar trips, and (ii) random forest classification. The random forest approach is able to achieve - $70-80% accuracy (purpose: 72%, mode: 79%, replaced mode: 81%). These novel approaches to trip classification allow us to increase the rate of user labeling by suggesting predicted labels to be verified by the user. Unlabeled trips can also contribute to aggregate analyses, using label predictions and their associated confidences as a substitute. While there exist other travel survey apps with the ability to infer travel choices, to our knowledge, this is the first paper to describe such a supervised system and rigorously evaluate it.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2020

Genetic algorithm for demand response: a stackelberg game approach

Demand response (DR) has gained a significant recent interest due to its potential for mitigating many power system problems. Game theory is a very effective tool to be utilized in DR management. In this paper, the DR between a distribution system operator (DSO) and load aggregators (LAs) is designed as a Stackelberg game, where the DSO acts as the leader and LAs are regarded as the followers. Due to the limitations of the centralized solution approaches, a genetic algorithm-based decentralized approach is proposed. To demonstrate the proposed approach, a case study concerning a day-ahead optimization for a real-time pricing market with a single DSO and three LAs is designed and optimized. The proposed approach is able to shift the demand peaks and prove that it has a great potential to be used for the Stackelberg game between a DSO and multiple LAs to fully exploit the potential of DR.

Amasyali, Kadir↗
DOE OSTI2021

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs

In simulation-based studies and analyses of epidemics, a major challenge lies in resolving the conflict between fidelity of models and the speed of their simulation. Another related challenge arises in dealing with the large number of what–if scenarios that need to be explored. Here, we describe new computational methods that together provide an approach to dealing with both challenges. A mesoscopic modeling approach is described that strikes a middle ground between macroscopic models based on coupled differential equations and microscopic models built on fine-grained behaviors at the individual entity level. The mesoscopic approach offers the ability to incorporate complex compositions of multiple layers of dynamics even while retaining the potential for aggregate behaviors at varying levels. It also is an excellent match to the accelerator-based architectures of modern computing platforms in which graphical processing units (GPUs) can be exploited for fast simulation via the parallel execution mode of single instruction multiple thread (SIMT). The challenge of simulating a large number of scenarios is addressed via a method of sharing model state and computation across a tree of what–if scenarios that are localized, incremental changes to a large base simulation. A combination of the mesoscopic modeling approach and the incremental what–if scenario tree evaluation has been implemented in the software on modern GPUs. Synthetic simulation scenarios are presented to demonstrate the computational characteristics of our approach. Results from the experiments with large population data, including USA, UK, and India, illustrate the modeling methodology and computational performance on thousands of synthetically generated what–if scenarios. Execution of our implementation scaled to 8192 GPUs of supercomputing platforms demonstrates the ability to rapidly evaluate what–if scenarios several orders of magnitude faster than the conventional methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

OpenSn: A massively parallel, open-source simulation environment for discrete ordinates radiation transport

OpenSn is an open-source, massively parallel deterministic radiation transport code for solving the discrete-ordinates ( S N ) form of the Boltzmann transport equation on unstructured, arbitrary polyhedral meshes. It supports high-fidelity simulations involving steady-state, eigenvalue, and adjoint problems for neutral particles (e.g., neutrons, photons, multi-particles), using the multigroup approximation in energy. OpenSn combines angular discretization via discrete ordinates with a discontinuous Galerkin finite element method (DGFEM) in space, enabling accurate resolution of transport physics on arbitrary polyhedral cells, included locally refined spatial grids. It includes multiple angular quadrature types, including locally refined angular quadratures. Written in modern C++ with a Python API, OpenSn runs efficiently on platforms ranging from laptops to supercomputers. The transport sweep algorithm is implemented using a task-based, directed-acyclic-graph (DAG) approach for each angle and supports asynchronous parallelism across thousands of MPI ranks. Group-set aggregation improves compute intensity, and synthetic acceleration techniques (e.g., diffusion synthetic acceleration, second-moment method) enhance solver convergence. OpenSn has been verified on reactor physics problems and demonstrated excellent weak and strong scaling performance on more than 32,768 processes, making it a versatile and robust platform for large-scale transport simulations in complex geometries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Emerging multiscale insights on microbial carbon use efficiency in the land carbon cycle

Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

An Optimization-Based HVAC Load and PV Disaggregation Methodology With Contextual Supervision

Here, this letter presents an optimization-based Heating, Ventilation, and Air Conditioning (HVAC) and PV disaggregation approach. This letter builds on the previous works of authors, which discuss HVAC disaggregation strategy for aggregated levels without requiring sub-metered information. This letter expands on previous works to discuss optimization-based HVAC disaggregation by varying PV penetration scenarios with joint disaggregation of HVAC load and PV.

Analytics↗
DOE OSTI2020

Silicon photonic chip for 16-channel wavelength division (de-)multiplexing in the O-band

We experimentally demonstrate a silicon photonic chip-scale 16-channel wavelength division multiplexer (WDM) operating in the O-band. The silicon photonic chip consists of a common-input bus waveguide integrated with a sequence of 16 spectral add-drop filters implemented by 4-port contra-directional Bragg couplers and resonant cladding modulated perturbations. The combination of these features reduces the spectral bandwidth of the filters and improves the crosstalk. An apodization of the cladding modulated perturbations between the bus and the add/drop waveguides is used to optimize the strength of the coupling coefficient in the propagation direction to reduce the intra-channel crosstalk on adjacent channels. The fabricated chip was validated experimentally with a measured intra-channel crosstalk of ∼−18.9 dB for a channel spacing of 2.6 nm. The multiplexer/demultiplexer chip was also experimentally tested with a 10 Gbps data waveform. The resulting eye-pattern indicates that this approach is suitable for datacenter WDM-based interconnects in the O-band with large aggregate bandwidths.

Davis, Jordan A. (ORCID:0000000343483295)↗
DOE OSTI2023

Advanced Laboratory and Field Arrays: Technical Report for Performance Enhancement for Marine Energy Converter (MEC) Arrays (Task 5)

Task 5 consisted of two parts, wave energy converter (WEC) arrays and current energy converter (CEC) arrays. The two parts of the project were executed independently, and this report covers only the work on WECs. In this part of the task, the team characterized the behavior of and developed control schemes for wave energy converter (WEC) arrays that improved performance (i.e., maximized aggregate power generation and reduced the levelized cost of energy) over baseline, non-coordinated control approaches. Specifically, for WEC arrays: the team developed optimal layouts of arrays that considered the effect of WEC placement within an array on coordinated array control with real-time estimation schemes. The numerical codes developed through this task were made available to users for array design. These tools utilized existing commercial software as well as software developed within the project team.

13 HYDRO ENERGY↗
DOE OSTI2025

Mapping and Synthesis of International Biomass Supply Assessments

This report, Mapping and Synthesis of International Biomass Supply Assessments (or Global Biomass Resource Assessment) is the first step in a long-term process to assemble data from around the globe into a virtual repository that can be updated and provide user-friendly access to the data. The Clean Energy Ministerial (CEM) Biofuture Platform Initiative recommended that research be completed to “address the need for internationally accepted benchmarks quantifying sustainable biomass feedstock supplies.” To act upon the CEM Biofuture recommendation, in 2024, the U.S. Department of Energy (DOE) commissioned Oak Ridge National Laboratory (ORNL) to prepare this report as the primary deliverable for a one-year assignment to assemble data into a citable form that could help resolve the persistent question presented related to bioenergy policy, “Is there enough sustainable biomass?” In response to that query, this report includes information received by August 2024 from national CEM representatives, collaborators, and public sources on current and future sustainable biomass supplies in 62 nations,and subsequently documents (a) the approach used by ORNL to analyze and categorize the information received in a manner that enables aggregation and comparability; and (b) recommendations for next steps and guidelines to help others update and harmonize future assessments of global sustainable biomass supplies.

09 BIOMASS FUELS↗
DOE OSTI2022

Harnessing Particle Size‐Control and DNA‐Oligo Functionalization in ZIF‐76 for Biological Applications

Abstract Advanced therapeutics require novel nanocarriers to ensure their functionality is preserved during transit. Zeolitic imidazolate frameworks (ZIFs) have emerged as promising materials in this field owing to their combined biocompatibility, high porosity, and tunable chemistry. While a diverse family of ZIFs has been reported, few have been explored beyond the prototypical ZIF‐8. Herein, the size‐controlled synthesis of three distinct ZIF‐76 analogs is demonstrated, overcoming the unique synthetic challenges intrinsic to the lta topology and complex crystallization kinetics associated with the mixed linker approach. This assesses the materials’ platform effectiveness for intracellular delivery first by exploring the structural and colloidal stability in biologically relevant media. To circumvent particle aggregation, fluorescently labeled DNA oligonucleotides are post‐synthetically attached to the ZIF surface. This modification significantly improves the colloidal stability in media and facilitates particle internalization tracking. Finally, the particle‐cell interactions are assessed, revealing rapid cell membrane association with macrophages, but not lung epithelial cells, and ZIF accumulation within macrophages which increased over time. Importantly, this study outlines a generalized approach toward expanding the available library of ZIFs for biological applications, enabling the potential for targeted therapeutic delivery for intracellular infections treatment.

Deneff, Jacob I.↗
DOE OSTI2025

Analyzing line-of-sight selection biases in galaxy-scale strong lensing with external convergence and shear

The upcoming Vera Rubin Observatory Legacy Survey of Space and Time (LSST) will dramatically increase the number of strong gravitational lensing systems, requiring precise modeling of line-of-sight (LOS) effects to mitigate biases in lensing observations and cosmological inferences. We develop a method to construct joint distributions of external convergence (κ ext ) and shear (γ ext ) for strong lensing LOS by aggregating large-scale structure simulations with high-resolution halo renderings and non-linear correction. Our approach captures both smooth background matter and perturbations from halos, enabling accurate modeling of LOS effects. Here, we apply non-linear LOS corrections to κ ext and γ ext that address the non-additive lensing effects caused by objects along the LOS in strong lensing. We find that, with a minimum image separation of 1.0'', non-linear LOS correction due to the presence of a dominant deflector slightly increases the ratio of quadruple to double lenses; this non-linear LOS correction also introduces systematic biases of ∼ 0.1% for galaxy-AGN lens in the inferred Hubble constant (H 0 ) if not accounted for. We also observe a 0.66% bias for galaxy-galaxy lenses on H 0 , and even larger biases 1.02% for galaxy-AGN systems if LOS effects are not accounted for. These results highlight the importance of LOS for precision cosmology. The publicly available code and datasets provide tools for incorporating LOS effects in future analyses.

Hubble constant↗
DOE OSTI2021

Leveraging Topological Events in Tracking Graphs for Understanding Particle Diffusion

Abstract Single particle tracking (SPT) of fluorescent molecules provides significant insights into the diffusion and relative motion of tagged proteins and other structures of interest in biology. However, despite the latest advances in high‐resolution microscopy, individual particles are typically not distinguished from clusters of particles. This lack of resolution obscures potential evidence for how merging and splitting of particles affect their diffusion and any implications on the biological environment. The particle tracks are typically decomposed into individual segments at observed merge and split events, and analysis is performed without knowing the true count of particles in the resulting segments. Here, we address the challenges in analyzing particle tracks in the context of cancer biology. In particular, we study the tracks of KRAS protein, which is implicated in nearly 20% of all human cancers, and whose clustering and aggregation have been linked to the signaling pathway leading to uncontrolled cell growth. We present a new analysis approach for particle tracks by representing them as tracking graphs and using topological events – merging and splitting, to disambiguate the tracks. Using this analysis, we infer a lower bound on the count of particles as they cluster and create conditional distributions of diffusion speeds before and after merge and split events. Using thousands of time‐steps of simulated and in‐vitro SPT data, we demonstrate the efficacy of our method, as it offers the biologists a new, detailed look into the relationship between KRAS clustering and diffusion speeds.

McDonald, T.↗
DOE OSTI2021

Diagnosing Malaria Patients with Plasmodium falciparum and vivax Using Deep Learning for Thick Smear Images

We propose a new framework, PlasmodiumVF-Net, to analyze thick smear microscopy images for a malaria diagnosis on both image and patient-level. Our framework detects whether a patient is infected, and in case of a malarial infection, reports whether the patient is infected by Plasmodium falciparum or Plasmodium vivax. PlasmodiumVF-Net first detects candidates for Plasmodium parasites using a Mask Regional-Convolutional Neural Network (Mask R-CNN), filters out false positives using a ResNet50 classifier, and then follows a new approach to recognize parasite species based on a score obtained from the number of detected patches and their aggregated probabilities for all of the patient images. Reporting a patient-level decision is highly challenging, and therefore reported less often in the literature, due to the small size of detected parasites, the similarity to staining artifacts, the similarity of species in different development stages, and illumination or color variations on patient-level. We use a manually annotated dataset consisting of 350 patients, with about 6000 images, which we make publicly available together with this manuscript. Our framework achieves an overall accuracy above 90% on image and patient-level.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Community Structure and Microbial Associations in Sediment-Free Methanotrophic Enrichment Cultures from a Marine Methane Seep

We report Syntrophic consortia of anaerobic methanotrophic archaea (ANME) and sulfate-reducing bacteria (SRB) consume large amounts of methane and serve as the foundational microorganisms in marine methane seeps. Despite their importance in the carbon cycle, research on the physiology of ANME-SRB consortia has been hampered by the slow growth and complex physicochemical environment the consortia inhabit. Here, we report successful sediment-free enrichment of ANME-SRB consortia from deep-sea methane seep sediments in the Santa Monica Basin, California. Anoxic Percoll density gradients and size-selective filtration were used to separate ANME-SRB consortia from sediment particles and single cells to accelerate the cultivation process. Over a 3-year period, a subset of the sediment-associated ANME and SRB lineages, predominantly comprised of ANME-2a/2b (“Candidatus Methanocomedenaceae”) and their syntrophic bacterial partners, SEEP-SRB1/2, adapted and grew under defined laboratory conditions. Metagenome-assembled genomes from several enrichments revealed that ANME-2a, SEEP-SRB1, and Methanococcoides in different enrichments from the same inoculum represented distinct species, whereas other coenriched microorganisms were closely related at the species level. This suggests that ANME, SRB, and Methanococcoides are more genetically diverse than other members in methane seeps. Flow cytometry sorting and sequencing of cell aggregates revealed that Methanococcoides, Anaerolineales, and SEEP-SRB1 were overrepresented in multiple ANME-2a cell aggregates relative to the bulk metagenomes, suggesting they were physically associated and possibly interacting. Overall, this study represents a successful case of selective cultivation of anaerobic slow-growing microorganisms from sediments based on their physical characteristics, introducing new opportunities for detailed genomic, physiological, biochemical, and ecological analyses. Biological anaerobic oxidation of methane (AOM) coupled with sulfate reduction represents a large methane sink in global ocean sediments. Methane consumption is carried out by syntrophic archaeal-bacterial consortia and fuels a unique ecosystem, yet the interactions in these slow-growing syntrophic consortia and with other associated community members remain poorly understood. The significance of this study is the establishment of sediment-free enrichment cultures of anaerobic methanotrophic archaea and sulfate-reducing bacteria performing AOM with sulfate using selective cultivation approaches based on size, density, and metabolism. By reconstructing microbial genomes and analyzing community composition of the enrichment cultures and cell aggregates, we shed light on the diversity of microorganisms physically associated with AOM consortia beyond the core syntrophic partners. These enrichment cultures offer simplified model systems to extend our understanding of the diversity of microbial interactions within marine methane seeps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Enhanced Photo-Cross-Linking of Thymines in DNA Holliday Junction-Templated Squaraine Dimers

Programmable self-assembly of dyes using DNA templates to promote exciton delocalization in dye aggregates is gaining considerable interest. New methods to improve the rigidity of the DNA scaffold and thus the stability of the molecular dye aggregates to encourage exciton delocalization are desired. In these dye–DNA constructs, one potential way to increase the stability of the aggregates is to create an additional covalent bond via photo-cross-linking reactions between thymines in the DNA scaffold. Specifically, we report an approach to increase the yield of photo-cross-linking reaction between thymines in the core of a DNA Holliday junction while limiting the damage from UV irradiation to DNA. We investigated the effect of the distance between thymines on the photo-cross-linking reaction yields by using linkers with different lengths to tether the dyes to the DNA templates. By comprehensively evaluating the photo-cross-linking reaction yields of dye–DNA aggregates using linkers with different lengths, we conclude that interstrand thymines tend to photo-cross-link more efficiently with short linkers. A higher cross-linking yield was achieved due to the shorter intermolecular distance between thymines influenced by strong dye–dye interactions. Furthermore, our method establishes the possibility of improving the stability of DNA-scaffolded dye aggregates, thereby expanding their use in exciton-based applications such as light harvesting, nanoscale computing, quantum computing, and optoelectronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗