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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Validated Models for Radiation Response and Signal Generation in Scintillators: Final Report

This Final Report presents work carried out at Pacific Northwest National Laboratory (PNNL) under the project entitled “Validated Models for Radiation Response and Signal Generation in Scintillators” (Project number: PL10-Scin-theor-PD2Jf) and led by Drs. Fei Gao and Sebastien N. Kerisit. This project was divided into four tasks: 1) Electronic response functions (ab initio data model) 2) Electron-hole yield, variance, and spatial distribution 3) Ab initio calculations of information carrier properties 4) Transport of electron-hole pairs and scintillation efficiency Detailed information on the results obtained in each of the four tasks is provided in this Final Report. Furthermore, published peer-reviewed articles based on the work carried under this project are included in Appendix. This work was supported by the National Nuclear Security Administration, Office of Nuclear Nonproliferation Research and Development (DNN R&D/NA-22), of the U.S. Department of Energy (DOE).

Environmental Molecular Sciences Laboratory↗
DOE OSTI2015

Status Report on the Water-Based NSTF RCCS Capability: Preparations and Design for the Transformation of the Natural Convection Shutdown Heat Removal Test Facility (NSTF) From Air to Water-based Cooling

The following report provides an overview of the current status of the water-based transformation, including details of the design, geometry, and fabrication of the test section and network piping, for the ½ scale water-based NSTF program at Argonne National Laboratory. In early FY2015, efforts towards a water-based design began in parallel with on-going air-based work, and began by identifying top level objectives of the transformation. Scaling studies and preparation tasks with computational modeling were carried out to guide the design decisions, minimize distortions, and ensure relevant data among scales. This entailed close collaboration with AREVA, whose water-based RCCS (included as part of their 625 MWt SC-HTGR) served as the primary design basis for incorporation into the NSTF. A literature review of previous works was made, with an emphasis placed on similar facilities, relevance to passive decay heat removal, and details pertaining to two-phase flow and measurement techniques. The study focused on input from key designers and a thermal analysis of existing cooling panels (e.g. at TAMU and UW-Madison) and two proposed AREVA cooling panels. A base case was used as a reference point for parametric studies of effects from varying tube spacing (pitch), tube diameter, fin thickness, and materials. Then, a structural analysis was performed to ensure safe material stresses during high temperature operation. Details of the pipe network geometry and guidelines for design of the water storage tank are finally presented, followed by engineering drawings in the appendix. The results of this study have identified a suitable configuration to support both the ANL/DOE project goals and the DOE vision to provide AREVA with data suitable for characterizing the RCCS of their full scale HTGR design. The dimensions were not selected for optimal RCCS performance, but instead to serve as a representative yet bounding configuration for future implementation into a full scale design. Scaling distortions are unavoidable; however, they can be accurately predicted based on earlier works of derived similarity solutions. Flexibility remained a primary design philosophy, and will allow the test facility to easily accommodate future alterations. The final design for the test section and network piping is as follows: riser tubes: 1.5” Schedule 160, 5.91” (150-mm) pitch, 304L stainless, heat transfer panels: 5/16” plates, 4.01” (102-mm) width, full penetration weld to risers, 304L stainless, split into 4 panels per riser separated by horizontal 1/8” gaps, test section: Eight (x8) riser tubes and nine (x9) heat transfer panels, fabricated into banks of two (x2) riser tubes and three (x3) fins, joined to form single section, and network geometry: 4.0” Schedule 40, 304L stainless. Details of the water storage tank will reflect competing effects such as thermal hydraulic phenomena during single and two-phase operation. These considerations include mixing during single-phase jet penetration, condensation of rising bubbles during two-phase discharge, bubble entrainment into the liquid outlet, and liquid carry-over into the steam outlet.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Extending the Roofline Model for Asynchronous Many-Task Runtimes

New architectural trends and extreme scale parallelism challenge the efficient mapping of applications to large scale and emerging systems. Fine-grained Asynchronous Manytask Runtimes (AMR) offer a unique flexibility to hide the varying latencies of contentious operations, and facilitate the effective exploitation of abundant resources. By decomposing work into smaller asynchronous chunks, the impact of unpredictable operations can be mitigated through a tighter overlapping of tasks. Unfortunately, the cost of this decomposition comes at a potentially steep price in the form of runtime overhead which can at times rival the cost of the computation itself. This leads to the question, how large should a task be? A common practice for application developers is to experimentally determine the granularity of a task after a code has been parallelized. Instead, we propose a new methodology based on an extended Roofline model to provide practical upper bounds on the throughput performance of an application. First, we extend the Roofline model to support not only latency hiding analysis, but also a multidimensional amortized analysis. By combining this new methodology with a serial application and an AMR implementation, we can predict the worst case runtime overhead attribution of individual runtime features prior to the development of parallel code. Thus, this runtimecentric methodology can provide a vehicle for application/runtime codesign by providing a comprehensive bottleneck analysis based on existing runtime features.

Suetterlein, Joshua D.↗
NASA NTRS2021

Advanced Air Mobility(AAM) Ecosystems Working Group Briefing Urban Air Mobility Noise Working Group (UNWG) Subgroup 2: Ground & Flight Testing

Overview of Urban Air Mobility Noise Working Group (UNWG) activities of Subgroup 2, responsible for developing Urban Air Mobility (UAM) vehicle ground and flight testing recommendations for those tasked with evaluating the acoustic characteristics of UAM vehicles under development. This topic is being briefed to an audience at the Advanced Air Mobility (AAM) Ecosystems Working Group Meeting (AEWG).

acoustics↗
NASA NTRS2018

NASA 2018 Green Propulsion Roadmap

The Green Propulsion Working Group (GPWG) is a technical guidance working group formed April 2017 under the Agency's Capability Leadership Team The GPWG was tasked with recommending an agency road map and providing guidance to NASA on green propulsion technology development and infusion The GPWG's efforts focus on ionic liquid propellants and related technologies The GPWG was chartered with three representatives from NASA Centers currently exploring green propulsion technologies As other Centers may explore programs that utilize green propulsion, membership of the working group can be expanded to include more interested parties Working group also solicits and coordinates with other government agencies (e.g. AFRL, MDA) In 2015, JANNAF hosted a Technical Interchange Meeting (TIM) on Green Monopropellant Alternatives to Hydrazine (GMAH) Included both Government and non-Government contributions on the State-of-the-Art in Green Propulsion Technology Following the TIM, a Government-only session (USAF/AFRL/NASA/MDA/DLA) reviewed and identified remaining technical gaps in Green Propulsion In 2016, an inter-agency team (AFRL/NASA/MDA) worked together to develop an informal inter-agency "roadmap" based on the outcome of the TIM Approach consisted of near-term, mid-term, and long-term technology advancement areas, approaching incrementally larger thrust classes The NASA Green Propulsion Working Group reviewed the work of the 2016 Inter-Agency Working Group, and concurs that the identified technical gaps and technology development areas are still relevant and necessary to see green propulsion technology advanced The GPWG recommends the 2016 roadmap be adopted as baseline for NASA needs, with some additions The focus of the 2016 inter-agency roadmap was primarily on the thruster technology. The Agency must also invest in understanding the broader propulsion system-level technology gaps in parallel. Timeframes are considered suggested from a priority standpoint, but are also flexible as some efforts will need to occur in the nearer term or concurrently in order to meet specific mission requirements The GPWG developed 2018 roadmap breaks down the technology development goals into Technology Development Areas (TDA's), and identifies the near-, mid, and long-term sub-goals within those areas. Those TDA's are: Thruster Hardware Development Modeling & Tools Development Materials Properties and Compatibility Propellant Development.

Cavender, Dan↗
NASA NTRS2004

Safety Aboard the International Space Station

As with any task that NASA takes on, safety is of utmost importaqce. There are pages of safety codes and procedures that must be followed before any idea can be brought to life. Unfortunately, the International Space Station s (ISS) safety regulations and procedures are based on lg standards rather than on Og. To aide in making this space age home away from home a less hazardous environment, I worked on several projects revolving around the dangers of flammable items in microgravity. The first task I was assigned was to track flames. This involves turning eight millimeter video recordings, of tests run in the five second drop tower, into avi format on the computer. The footage is then compressed and altered so that the flame can be seen more clearly. Using another program called Spotlight, line profiles were used to collect data describing the luminescence of the flame at different points. These raw data are saved as text files and run trough a macro so that a Matlab program can analyze it. By fitting the data to a curve and determining the areas of brightest luminescence, the behavior of the flame can be recorded numerically. After entering the data into a database, researchers can come back later and easily get information on flames resulting from different gas and liquid mixtures in microgravity. I also worked on phase two of the FATE project, which deals with safety aboard the ISS. This phase involves igniting projected droplets and determining how they react with secondary materials. Such simulations represent, on a small scale, the spread of onboard fires due to the effervescence of burning primary materials. I set up existing hardware to operate these experiments and ran tests with it, photographing the results. I also made CAD drawings of the apparatus and the area available on the (SF)2 rig for it to fit into. The experiment will later be performed on the KC-135, and the results gathered will be used to reanalyze current safety standards for the ISS, including the distance of required separation for flammable materials. Additional information is included in the original extended abstract.

Mintz, Shauna M.↗
DOE OSTI2023

Simultaneous Improvements in Efficiency and Stability of Organic Solar Cells via a Symmetric‐Asymmetric Dual‐Acceptor Strategy

Abstract Simultaneously achieving improvements in power conversion efficiency (PCE) and stability is the main task of the current development stage of organic solar cells (OSCs). This work reports a symmetry–asymmetry dual‐acceptor (SADA) strategy to construct ternary devices, which is found to be feasible for increasing both the PCE and the operational lifetime of OSCs. In this contribution, the symmetric acceptor L8‐BO and the asymmetric acceptor BTP‐S9 are blended in equal proportions with polymer donor PM6 for the consideration of absorption spectrum complementarity and cascade energetic alignment. In addition, the features of crystallinity and miscibility of the dual‐acceptor deliver optimized morphology lead to a high PCE of 18.84%. In addition, the asymmetric acceptor BTP‐S9 with a larger dipole moment shows tighter molecular stacking and longer crystal correlation length, which favor intrinsic molecular photostability, and further consolidate the operational lifetime of OSCs when coordinated with L8‐BO. This work demonstrates the efficacy of the SADA strategy for constructing efficient and stable OSCs.

Chemistry↗
DOE OSTI2021

Performance of Julia for High Energy Physics Analyses

We argue that the Julia programming language is a compelling alternative to currently more common implementations in Python and C++ for common data analysis workflows in high energy physics. We compare the speed of implementations of different workflows in Julia with those in Python and C++. Furthermore, our studies show that the Julia implementations are competitive for tasks that are dominated by computational load rather than data access. For work that is dominated by data access, we demonstrate an application with concurrent file reading and parallel data processing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Robotics for HVAC applications: A critical review and future perspectives

Recent advances in artificial intelligence (AI), enhanced computational capabilities, and innovations in sensors and hardware have driven the increasing development and application of robots in heating, ventilation, and air conditioning (HVAC) systems. We selected and reviewed 101 studies published between 2005 and 2025, sourced from IEEE Xplore, Scopus, Web of Science, and the ACM Digital Library. To analyze these works, we developed a five-dimensional analytical framework (morphology, sensing, navigation, task execution, and system integration), inspired by the Springer Handbook of Robotics and tailored specifically for robotic applications in HVAC. Based on the reviewed studies, six distinct tasks spanning the entire HVAC lifecycle have been identified. Among the six tasks, inspection and maintenance dominate (59 %), followed by indoor monitoring and auditing (21 %), whereas leakage detection, comfort support, and installation/retrofit remain less explored. To address the identified gaps, this review proposes future research directions including investigating robot-aware HVAC design principles, developing multimodal HVAC sensing and data fusion techniques, enhancing robot training and hardware capabilities, and expanding robotic applications beyond Maintenance and Operations (M&O). The findings from this review inform future robotics research for HVAC applications and ultimately enhance system affordability, energy efficiency, resilience or reliability, and occupant environmental comfort. Moreover, it seeks to inspire researchers to explore the intersections of robotics, computer science, building science, and HVAC engineering fostering advancements in this multidisciplinary field.

AI↗
DOE OSTI2015

Guided basin-hopping search of small boron clusters with density functional theory

The search for the ground state structures of Boron clusters has been a difficult computational task due to the unique metalloid nature of Boron atom. Previous research works had overcome the problem in the search of the Boron ground-state structures by adding symmetry constraints prior to the process of locating the local minima in the potential energy surface (PES) of the Boron clusters. In this work, we shown that, with the deployment of a novel computational approach that incorporates density functional theory (DFT) into a guided global optimization search algorithm based on basin-hopping, it is possible to directly locate the local minima of small Boron clusters in the PES at the DFT level. The ground-state structures search algorithm as proposed in this work is initiated randomly and needs not a priori symmetry constraint artificially imposed throughout the search process. Small sized Boron clusters so obtained compare well to the results obtained by similar calculations in the literature. The electronic properties of each structures obtained are calculated within the DFT framework.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Parameter extraction for a SPICE model of an hTron superconducting thermal switch

Efficiently simulating large circuits is crucial to the development of superconducting nanowire-based electronics. However, current simulation tools for this technology are not adapted to the scaling of circuit size and complexity. We focus on the multilayered heater-nanocryotron (hTron), a promising superconducting nanowire-based switch used in applications such as superconducting nanowire single-photon detector readout. Previously, the hTron was modeled using traditional finite-element methods, which fall short in simulating systems at a larger scale. An empirical-based method would be better adapted to this task, enhancing both simulation speed and agreement with experimental data. In this work, we perform switching current and activation delay measurements on 17 hTron devices. We then develop a method for extracting physical fitting parameters used to characterize the devices. We build a SPICE behavioral model that reproduces the static and transient device behavior using these parameters, and validate it by comparing its performance to a model developed in prior work, showing an improvement in simulation time by several orders of magnitude. Furthermore, our model provides circuit designers with a tool to help understand the hTron’s behavior during all design stages, thus enabling broader use of the hTron across various new areas of application.

Caloritronics↗
DOE OSTI2018

Revealing the role of electron-electron correlations by mapping dissociation of highly excited D 2 + using ultrashort XUV pulses

Understanding electron-electron correlations in matter ranging from atoms to solids represents a grand challenge for both experiment and theory. Here, these correlations occur on attosecond timescales and have only recently become experimentally accessible. In the case of highly excited systems, the task of understanding and probing correlated interactions is even greater. In this work, we combine state-of-the-art light sources and advanced detection techniques with ab initio calculations to unravel the role of electron-electron correlation in D 2 photoionization by mapping the dissociation of a highly excited D 2 + molecule. Correlations between the two electrons dictate the pathways along which the molecule dissociates and lead to a superposition of excited ionic states. Using 3D Coulomb explosion imaging and electron-ion coincidence techniques, we assess the relative contribution of competing parent ion states to the dissociation process for different orientations of the molecule with respect to the laser polarization, which is consistent with a shake-up ionization process. As a step toward observing coherent superposition experimentally, we map the relevant nuclear potentials using Coulomb explosion imaging and show theoretically that such an experiment could confirm this coherence via two-path interference.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Application of machine learning in the determination of impact parameter in the 132 Sn+ 124 Sn system

Here, 132 Sn + 124 Sn collisions at a beam energy of 270 MeV/nucleon were performed at the Radioactive Isotope Beam Factory (RIBF) in RIKEN to investigate the nuclear equation of state. Reconstructing the impact parameter is one of the important tasks in the experiment as it relates to many observable. In this work, we employ three commonly used algorithms in machine learning, the artificial neural network (ANN), the convolutional neural network (CNN), and the light gradient boosting machine (LightGBM), to determine the impact parameter by analyzing either the charged particle spectra or several features simulated with events from the ultrarelativistic quantum molecular dynamics (UrQMD) model. To closely imitate experimental data and investigate the generalizability of the trained machine learning algorithms, incompressibility of nuclear equation of state and the in-medium nucleon-nucleon cross sections are varied in the UrQMD model to generate the training data. The mean absolute error Δb between the true and the predicted impact parameter is smaller than 0.45 fm if training and testing sets are sampled from the UrQMD model with the same parameter set. However, if training and testing sets are sampled with different parameter sets, Δb would increase to 0.8 fm. The generalizability of the trained machine learning algorithms suggests that these machine learning algorithms can be used reliably to reconstruct the impact parameter in experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Accelerating Scientific Workflows on HPC Platforms with In Situ Processing

Scientific workflows drive most modern large-scale science breakthroughs by allowing scientists to define their computations as a set of jobs executed in a given order based on their data dependencies. Workflow management systems (WMSs) have become key to automating scientific workflows-executing computational jobs and orchestrating data transfers between those jobs running on complex high-performance computing (HPC) platforms. Traditionally, WMSs use files to communicate between jobs: a job writes out files that are read by other jobs. However, HPC machines face a growing gap between their storage and compute capabilities. To address that concern, the scientific community has adopted a new approach called in situ, which bypasses costly parallel filesystem I/O operations with faster in-memory or in-network communications. When using in situ approaches, communication and computations can be interleaved. In this work, we leverage the Decaf in situ dataflow framework to accelerate task-based scientific workflows managed by the Pegasus WMS, by replacing file communications with faster MPI messaging. We propose a new execution engine that uses Decaf to manage communications within a sub-workflow (i.e., set of jobs) to optimize inter-job communications. We consider two workflows in this study: (i) a synthetic workflow that benchmarks and compares file- and MPI-based communication; and (ii) a realistic bioinformatics workflow that computes mu-tational overlaps in the human genome. Experiments show that in situ communication can improve the bioinformatics workflow execution time by 22% to 30% compared with file communication. Our results motivate further opportunities and challenges for bridging traditional WMSs with in situ frameworks.

Decaf↗
DOE OSTI2022

Exploring Tradeoffs in Federated Learning on Serverless Computing Architectures

Federated learning is driving the development of new techniques to efficiently and securely use data across multiple sites while using diverse resources. One of these techniques is the use of the serverless computing paradigm to abstract away resource specific configurations, allowing federated learning across heterogeneous environments. However, deploying federated learning across edge resources, the cloud, and traditional HPC sites will require specialized approaches in order to best account for the weaknesses and strengths of each resource. In this work, we explore the new tradeoffs presented by managing a federated learning task across heterogeneous resources and demonstrate these tradeoffs with experiments using a serverless federated learning framework.

Baughman, Matt↗
DOE OSTI2022

Sparse Deep Neural Network Inference using different Programming Models

Sparse deep neural networks have gained increasing attention recently in achieving speedups on inference with reduced memory footprints. However, the real-world applications are little shown with specialized optimizations, yet a wide variety of DNN tasks remain dense without exploiting the advantages of sparsity in networks. Recent work presented by MIT/IEEE/Amazon GraphChallenge has demonstrated significant speedups and various techniques. Still, we find that there is limited investigation of the impact of various Python and C\slash C++ based programming models to explore new opportunities in general cases. In this work, we provide performance evaluation through different programming models using CuPy, cuSPARSE, and OpenMP to discuss the advantages and disadvantages of our sparse implementations on single-GPU and multiple GPUs of NVIDIA DGX-A100 40GB/80GB platforms.

machine learning, HPC↗
DOE OSTI2024

Transmission Data-Driven User-Defined Model for Inverter-based and Conventional Power Plants

Recent events in Odessa [1], [2] have shed light on the complexities of integrating large Inverter-Based Resource (IBR) plants with the transmission system, prompting NERC to stress continuous performance monitoring by transmission operators. Challenges such as plant control updates, IBR model revisions, Phase-locked loop loss of synchronism, and protection events have been identified, underscoring the need for enhanced monitoring protocols by regulatory bodies. The recent FERC 901 order underscores the importance of accurate data exchange regarding IBRs for reliability studies. However, limited access to IBR plant-related data hampers effective decision-making for transmission operators (TOP). This paper proposes a method for constructing data-driven User-Defined dynamic Models (UDM) for power plants for validating multiple-event data using field measurements from interconnection bus locations. The problem is formulated as a power plant model identification problem and a multi-task learning approach under partial input observability assumptions is proposed in this work. This approach aims to predict aggregated responses of conventional and IBR power plants during various dynamic physical events which is useful for planning studies under diverse disturbance conditions. Ultimately, this methodology emphasizes the importance of plant visibility to operators in addressing power system challenges, facilitating improved planning and operational studies.

Mahapatra, Kaveri [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2016

Quantifying element incorporation in multispecies biofilms using nanoscale secondary ion mass spectrometry image analysis

Elucidating nutrient exchange in microbial communities is an important step in understanding the relationships between microbial systems and global biogeochemical cycles, but these communities are complex and the interspecies interactions that occur within them are not well understood. Phototrophic consortia are useful and relevant experimental systems to investigate such interactions as they are not only prevalent in the environment, but some are cultivable in vitro and amenable to controlled scientific experimentation. Nanoscale secondary ion mass spectrometry (NanoSIMS) is a powerful, high spatial resolution tool capable of visualizing the metabolic activities of single cells within a biofilm, but quantitative analysis of the resulting data has typically been a manual process, resulting in a task that is both laborious and susceptible to human error. In this work, the authors describe the creation and application of a semiautomated image-processing pipeline that can analyze NanoSIMS-generated data, applied to phototrophic biofilms as an example. The tool employs an image analysis process, which includes both elemental and morphological segmentation, producing a final segmented image that allows for discrimination between autotrophic and heterotrophic biomass, the detection of individual cyanobacterial filaments and heterotrophic cells, the quantification of isotopic incorporation of individual heterotrophic cells, and calculation of relevant population statistics. The authors demonstrate the functionality of the tool by using it to analyze the uptake of 15 N provided as either nitrate or ammonium through the unicyanobacterial consortium UCC-O and imaged via NanoSIMS. The authors found that the degree of 15N incorporation by individual cells was highly variable when labeled with 15 NH 4 + , but much more even when biofilms were labeled with 15 NO 3 – . In the 15 NH 4 + -amended biofilms, the heterotrophic distribution of 15 N incorporation was highly skewed, with a large population showing moderate 15 N incorporation and a small number of organisms displaying very high 15 N uptake. The results showed that analysis of NanoSIMS data can be performed in a way that allows for quantitation of the elemental uptake of individual cells, a technique necessary for advancing research into the metabolic networks that exist within biofilms with statistical analyses that are supported by automated, user-friendly processes.

59 BASIC BIOLOGICAL SCIENCES↗