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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Temporal coherent control of resonant two-photon double ionization of the hydrogen molecule via doubly excited states

Here, we use time-delayed, counter-rotating, circularly polarized few-cycle attosecond nonoverlapping pulses to study the temporal coherent control of the resonant process of two-photon double ionization (TPDI) of hydrogen molecule via doubly excited states for pulse propagation direction along $\hat k$ either parallel or perpendicular to the molecular axis $\hat R$. For $\hat k$∥ $\hat R$ and a pulse carrier frequency of 36 eV resonantly populating the Q 2 1 Π$^+_u$ (1) doubly excited state as well as other 1 Π$^+_u$ doubly excited states, we find that the indirect ionization pathway through these doubly excited states changes the character of the kinematical vortex-shaped momentum distribution produced by the two direct ionization pathways from fourfold to twofold rotational symmetry. This result is similar to what found in TPDI of the He atom involving 1 P$^ o_ {±1}$ doubly excited states; however, angular distributions exhibiting a quantum beat effect between the ground state and a doubly excited state seen for the He atom are observed here for its molecular counterpart with an anomaly in shape and magnitude, not in frequency. The sixfold differential probability integrated over the azimuthal angle of the photoelectron pair shows that this anomaly is due to autoionization decays and quantum beats between doubly excited states. For $\hat k$⟂$\hat R$ and a broadband pulse carrier frequency of 30 eV populating the Q 1 1 Π$^+_u$(1), Q 1 1 Σ$^+_u$(1), Q 2 1 Π$^+_u$(1) , and Q 1 1 Σ$^+_u$ (2) doubly excited states, the momentum distribution is shown to exhibit dynamical electron vortices with four spiral arms, which originates from the interplay between the 1 Δ$^+_ g$ , 1 Π$^+_ g$, and 1 Σ$^+_ g$ dynamical ionization amplitudes. Our treatment within either the adiabatic-nuclei approximation or fixed-nuclei approximation shows that the latter provides a very good account for this correlated process.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

ChatMPI: LLM-Driven MPI Code Generation for HPC Workloads

The Message Passing Interface (MPI) standard plays a crucial role in enabling scientific applications for parallel computing and is an essential component in high-performance computing (HPC). However, implementing MPI code manually—especially applying a proper domain decomposition and communication pattern—is a challenging and error-prone task. We present ChatMPI, an AI assistant for MPI parallelization of sequential C codes. In our analysis, we focus on testing six essential HPC workloads, which are based on Basic Linear Algebra Subprograms levels 1, 2, and 3 as well as sparse, stencil, and iterative operations. We analyze the process of creating ChatMPI by using the ChatHPC library. This lightweight large language model (LLM)–based infrastructure enables HPC experts to efficiently create and supervise trustworthy AI capabilities for critical HPC software tasks. We study the data required for training (fine-tuning) ChatMPI to generate parallel codes that not only use MPI syntax correctly but also apply HPC techniques to reduce memory communication and maximize performance by using proper work decomposition. With a relatively small training dataset composed of a few dozen prompts and fewer than 15 minutes of fine-tuning on one node equipped with two NVIDIA H100 GPUs, ChatMPI elevates trustworthiness for MPI code generation of current LLMs (e.g., Code Llama, ChatGPT-4o and ChatGPT 5). Additionally, we evaluate the performance of the MPI codes generated by ChatMPI in comparison with the ones generated by ChatGPT-4o and ChatGPT-5. The codes generated by ChatMPI provide up to a 4 × boost in performance by using better problem decomposition, communication patterns, and HPC techniques (e.g., communication avoiding).

Valero Lara, Pedro [ORNL] (ORCID:0000000214794310)↗
DOE OSTI2020

Carbon Cycling, Environmental & Rural Economic Impacts of Collecting & Processing Specific Woody Feedstocks in Biofuels

Woody biomass will be an essential feedstock for a large-scale cellulosic biofuel industry. The life cycle carbon accounting for the production of biofuels from woody feedstocks is complex and has engendered significant controversy. Issues such as below ground carbon, carbon debt, varied regional forest practices, multiple parallel forest product lines, and development of realistic counterfactual scenarios all contribute to the complexity. DOE funded CORRIM to develop comprehensive and definitive lifecycle inventories and assessments on the production of fuels from woody feedstocks. CORRIM brought together expertise in forest practices, short rotation woody crops, bioconversion of woody biomass, process modeling, and life cycle assessment to successfully accomplish this goal. The CORRIM team has developed data on forest productivity, fuel usage, and fuel production for six regionally specific forest systems. These six forest systems include three current commercial systems; southern pine plantations, Douglas-fir plantations, naturally regenerated Northeastern (NE) spruce/fir, and three ‘short rotation woody crops’, poplar, eucalyptus and willow, which are at different stages of demonstration in the US. The fuel production systems include cellulosic ethanol and bio-oil based hydrocarbons. The project was successfully reviewed at the BETO Program review in March 2015, 2017, and 2019 and has resulted currently in 19 publications and reports and 35 presentations at both national and international conferences, with more in the pipeline. See publications and presentations for links to each document. Finally, and most importantly, CORRIM has gone beyond the scope of the original DOE proposal to work closely with GREET at Argonne National Laboratory (ANL) to incorporate all the life cycle data and scenario models into their modeling system. GREET is the most widely used and definitive information source for evaluating lifecycle carbon emissions for fuels. The incorporation of CORRIM data from this project guarantees the results of the research will be extensively used and widely disseminated. Technical process improvements and policy relevant accomplishments are detailed in the relevant programmatic sections in the full report including citations therein. Highlights are summarized here for easy reference.

09 BIOMASS FUELS↗
DOE OSTI2025

RLGBS: Reinforcement Learning-Guided Beam Search for process optimization in a paper machine dryer section

Paper drying is responsible for over two-thirds of energy consumption in the U.S. pulp and paper industry, presenting significant potential for energy savings through optimization of process parameters. Current approaches often assume fixed operating conditions, neglecting dynamic ambient and process variations that limit achievable savings and real-world applicability. To this end, we develop a physics-based simulation environment for a paper machine dryer section and propose a reinforcement learning (RL) framework to minimize overall energy consumption by optimizing drying process parameters under diverse operating conditions. To mitigate overdrying and numerical instabilities caused by suboptimal local RL actions, we introduce Reinforcement Learning-Guided Beam Search (RLGBS), which explores multiple action sequences in parallel using beam search. Instead of making step-by-step decisions, RLGBS prioritizes solutions based on cumulative probability, reducing the impact of individual suboptimal actions. Experiments demonstrate that RLGBS achieves consistent energy savings under unseen operating conditions not encountered during training, outperforming conventional RL methods. While validated in drying optimization, this framework is broadly applicable to other RL-based industrial process control problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A Modeling Tool to Analyze the Performance of Industrial Cooling Towers

Energy efficiency and energy savings have become an important factor as industries look for ways to save energy and minimize their energy consumption while reducing their carbon footprint. Cooling towers are utilized significantly in industries for either serving chillers or process cooling. Depending on the size of the cooling tower, it can use a surprising amount of energy and water, which is why it is crucial to make sure that the facility has optimized their cooling tower.A modeling tool has been developed to perform a thorough analysis of a cooling tower and its various operations to ensure that the facility has optimized its cooling tower. This model analyzes an annual base case in comparison with the revised case of a cooling tower operation. This modeling tool simulates 8,760 hourly calculations for fan power for various fan controls, water consumption, and pumping energy consumption and demand based on the user’s location and its corresponding Typical Meteorological Year 3 (TMY3) weather data. This model is capable to simulate up to five cooling tower cells as one large tower utilizing one pump or parallel pumping. The successful validated cooling tower model should assist industry to save energy at their facility through their cooling tower, whether they use it for process cooling or heating, ventilation and air conditioning (HVAC) applications. The entering/leaving water temperatures based on a monthly operating schedule or a wet-bulb temperature schedule will be used as inputs, and the model can calculate savings in energy for various conditions including variable-frequency drive (VFD) on the fan/pump, drift eliminators, number of cycles of concentration, reduced water flow rate, etc.

Hooper, Josh↗
DOE OSTI2023

Acoustic‐Modulated, Selective Particle Deposition for Muti‐Material Additive Manufacturing

Powder‐based additive manufacturing (AM) is an important technology in fabricating complex 3D products. In powder‐based AM, a powder deposition system plays a key role in determining the resolution, density, and properties of printed parts. An acoustic‐actuated particle deposition approach, which utilizes acoustic waves to actuate a glass nozzle, enables the deposition of particles in a cost‐effective way. However, the capability to programmably deposit different particles using acoustic waves has yet to be fully demonstrated. Herein, a selective particle deposition approach via acoustic modulation for muti‐material AM is demonstrated. Sequential and parallel depositions of two types of particles by modulating the signal inputs and resonant frequencies of piezo transducers are demonstrated. An AM process is demonstrated by integrating this acoustic‐actuated particle deposition approach with a heat‐curing mechanism. Several products from this system are produced as well. It is expected that this particle deposition approach can be used in a wide spectrum of applications, such as direct manufacturing of multi‐functional materials/devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Scalable Data-Intensive Geocomputation: A Design for Real-Time Continental Flood Inundation Mapping

The convergence of data-intensive and extreme-scale computing enables an integrated software and data ecosystem for scientific discovery. Developments in this realm will fuel transformative research in data-driven interdisciplinary domains. Geocomputation provides computing paradigms in Geographic Information Systems (GIS) for interactive computing of geographic data, processes, models, and maps. Because GIS is data-driven, the computational scalability of a geocomputation workflow is directly related to the scale of the GIS data layers, their resolution and extent, as well as the velocity of the geo-located data streams to be processed. Unique in high user interactivity and low end-to-end latency requirements, geocomputation applications will dramatically benefit from the convergence of high-end data analytics (HDA) and high-performance computing (HPC). The application level challenge, however, is to identify and eliminate computational bottlenecks that arise along a geocomputation workflow. Indeed, poor scalability at any of the workflow components is detrimental to the entire end-to-end pipeline. Here, we study a large geocomputation use case in flood inundation mapping that handles multiple national-scale geospatial datasets and targets low end-to-end latency. We discuss benefits and challenges for harnessing both HDA and HPC for data-intensive geospatial data processing and intensive numerical modeling of geographic processes. We propose an HDA+HPC geocomputation architecture design that couples HDA (e.g., Spark)-based spatial data handling and HPC-based parallel data modeling. Key techniques for coupling HDA and HPC to bridge the two different software stacks are reviewed and discussed.

Liu, Yan↗
DOE OSTI2025

Scalable training of trustworthy and energy-efficient predictive graph foundation models for atomistic materials modeling: a case study with HydraGNN

We present our work on developing and training scalable, trustworthy, and energy-efficient predictive graph foundation models (GFMs) using HydraGNN, a multi-headed graph convolutional neural network architecture. HydraGNN expands the boundaries of graph neural network (GNN) computations in both training scale and data diversity. It abstracts over message passing algorithms, allowing both reproduction of and comparison across algorithmic innovations that define nearest-neighbor convolution in GNNs. This work discusses a series of optimizations that have allowed scaling up the GFMs training to tens of thousands of GPUs on datasets consisting of hundreds of millions of graphs. Our GFMs use multitask learning (MTL) to simultaneously learn graph-level and node-level properties of atomistic structures, such as energy and atomic forces. Using over 154 million atomistic structures for training, we illustrate the performance of our approach along with the lessons learned on two state-of-the-art US Department of Energy (US-DOE) supercomputers, namely the Perlmutter petascale system at the National Energy Research Scientific Computing Center and the Frontier exascale system at Oak Ridge Leadership Computing Facility. The HydraGNN architecture enables the GFM to achieve near-linear strong scaling performance using more than 2000 GPUs on Perlmutter and 16,000 GPUs on Frontier.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Demonstrating Cross-Facility Data Processing at Scale with Laue Microdiffraction

In February and April 2023 live, at-scale data processing demonstrations were conducted between the Advanced Photon Source (APS), a synchrotron light source, and the Argonne Leadership Computing Facility (ALCF). These tests were run as part of a novel beamline technique: coded aperture laue micro-diffraction. This technique requires a significant amount of compute to decode appeture patterns embedded in the detector stream. An autonomous system was able to send data to ALCF during an experiment, utilize 50 nodes of the Polaris supercomputer to process 6-12 hour scans, and return the data back to the APS within 12-15 minutes behind the detector. With scan points arriving every 72 seconds, the system kept up with the beamline, potentially enabling in-experiment analysis. The data processing system utilizes Globus infrastructure and an on-demand queue to dynamically acquire nodes on Polaris. The underlying reconstruction algorithms were parallelized via MPI and accelerated with custom CUDA kernels.

Prince, Michael↗
DOE OSTI2020

Device for controlling additive manufacturing machinery

A computing device for controlling the operation of an additive manufacturing machine comprises a memory element and a processing element. The memory element is configured to store a three-dimensional model of a part to be manufactured, wherein the three-dimensional model defines a plurality of cross sections of the part. The processing element is in communication with the memory element. The processing element is configured to receive the three-dimensional model, determine a plurality of paths, each path including a plurality of parallel lines, determine a radiation beam power for each line, such that the radiation beam power varies non-linearly according to a length of the line, and determine a radiation beam scan speed for each line, such that the radiation beam scan speed is a function of a temperature of a material used to manufacture the part, the length of the line, and the radiation beam power for the line.

Barr, Christian↗
DOE OSTI2020

Device for controlling additive manufacturing machinery

A computing device for controlling the operation of an additive manufacturing machine comprises a memory element and a processing element. The memory element is configured to store a three-dimensional model of a part to be manufactured, wherein the three-dimensional model defines a plurality of cross sections of the part. The processing element is in communication with the memory element. The processing element is configured to receive the three-dimensional model, determine a plurality of paths, each path including a plurality of parallel lines, determine a radiation beam power for each line, such that the radiation beam power varies non-linearly according to a length of the line, and determine a radiation beam scan speed for each line, such that the radiation beam scan speed is a function of a temperature of a material used to manufacture the part, the length of the line, and the radiation beam power for the line.

Barr, Christian↗
DOE OSTI2024

A Measurement of the Eta Meson Radiative Decay Width via the Primakoff Effect

The ? meson is an interesting tool to study fundamental symmetries in Quantum Chromodynamics (QCD). In particular, its radiative decay width, ? p? Ñ ??q, is an important quantity that can be predicted in the framework of Chiral Perturbation Theory. A precision measurement of this quantity would provide critical inputs to understanding the mixing of the ? and ?1 mesons and extracting constants with wide-ranging applications in low-energy QCD. This decay width has been measured in the past using two different experimental techniques. The more popular technique utilized e`e´ collisions to produce ? mesons through electromagnetic interactions. Today, the Particle Data Group (PDG) averages the results of five such experiments to obtain their currently-accepted value of the decay width as: 0.515?0.018 keV. However the first measurement of this quantity was obtained from a fixed-target experiment that measured the cross section for photoproduction of ? mesons on a nuclear target via the Primakoff effect. Their result of 0.324?0.046 keV shows strong tension with the average of the collider measurements, motivating a new, high precision measurement using the Primakoff method. For this purpose, the PrimEx-eta experiment was conducted in Hall D of the Thomas Jefferson National Accelerator Facility (Jefferson Lab or JLab). The data is currently being analyzed to measure the differential cross section for the photoproduction of ? mesons on a liquid, 4He target. Preliminary results obtained from the analysis of the first phase of the PrimEx-eta experiment show reasonable agreement with the currently-accepted PDG value of the radiative decay width. However, as will be discussed, there are many challenges to this precision measurement which must be studied before any results can be finalized and compared with previous measurements. In parallel to the ? decay width measurement, the PrimEx-eta experiment measured the total cross section for the fundamental, Quantum Electrodynamics (QED) process of Compton scattering from the atomic electrons inside the target. The results obtained from this measurement are in strong agreement with the next-to-leading order QED calculations, and the total combined uncertainties are below 3% for incident photon energies between 7-10 GeV. In addition to providing the first precision measurement of the total Compton scattering cross section within this beam energy range, this measurement verifies the capability of the PrimEx-eta experimental setup to perform absolute cross section measurements at forward angles, and serves as a reference process for the calibration of systematic uncertainties.

Smith, Andrew↗
DOE OSTI2024

Intrinsic Toroidal Rotation Driven by Turbulent and Neoclassical Processes in Tokamak Plasmas from Global Gyrokinetic Simulations

Gyrokinetic tokamak plasmas can exhibit intrinsic toroidal rotation driven by the residual stress. While most studies have attributed the residual stress to the parallel-momentum flux from the turbulent E × B motion, the parallel-momentum flux from the drift-orbit motion (denoted $Π^D_\parallel$) and the E × B-momentum flux from the E × B motion (denoted $Π_{E×B}$) are often neglected. Here, we use the global total-f gyrokinetic code XGC to study the residual stress in the core and the edge of a DIII-D H-mode plasma. Numerical results show that both $Π^D_\parallel$ and $Π_{E×B}$ make up a significant portion of the residual stress. In particular, $Π^D_\parallel$ in the core is higher than the collisional neoclassical level in the presence of turbulence, while in the edge it represents an outflux of countercurrent momentum even without turbulence. Using a recently developed “orbit-flux” formulation, we show that the higher-than-neoclassical-level $Π^D_\parallel$ in the core is driven by turbulence, while the outflux of countercurrent momentum from the edge is mainly due to collisional ion orbit loss. In conclusion, these results suggest that $Π^D_\parallel$ and $Π_{E×B}$ can be important for the study of intrinsic toroidal rotation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Electrocatalytic Valorization into H2 and Hydrocarbons of an Aqueous Stream Derived from Hydrothermal Liquefaction

Electrocatalytic oxidation is an attractive process for valorizing the carbon and removal of nitrogen present in the aqueous waste streams at ambient conditions. Here, we evaluated the electrocatalytic oxidation as a function of applied potential over a commercial Pt electrode of aqueous waste stream generated via hydrothermal liquefaction. We validated the conversion of quantifiable carbon (e.g., carboxylic acids, alpha hydroxyacids, alcohols, ketones, amides) and unquantifiable carbon as well as nitrogen removal. The unquantifiable carbon was valorized to quantifiable short chain organic molecules (e.g., acetic). Model studies showed that carboxylic acids, alcohol and ketones converted following (non-) Kolbe chemistry. Amides and alpha hydroxyacids formed carboxylic acids that subsequently converted via (non-) Kolbe chemistry. Ammonia was oxidized into N2. The reaction rate varied for each molecule family with carboxylic acids and ammonia having the highest reaction rates. The main reaction products from the electrocatalytic oxidation at the anode were volatile, short chain hydrocarbons (i.e., olefins, paraffins) and CO generated via Kolbe chemistry, while H2 was generated at the cathode. The parallel denitrification, valorization of carbon, and H2 generation of the aqueous waste can replace and simplify the current unit operations used in a commercial hydrothermal liquefaction process. The high operation potential required to drive the electrocatalytic reaction is responsible for high operation costs; however, they can be either partially subsidized with sale of excess H2 at the current DOE goal of $2/kg H2. Thus, the present work shows how electrocatalytic oxidation can be used to valorize aqueous waste streams into volatile hydrocarbons and H2.

Electrocatalytic oxidation, Aqueous waste valoriza↗
DOE OSTI2024

Frequency-domain computing using nonlinear acoustic-wave device on lithium niobate

Abstract Multiply-accumulation are crucial computing operations in signal processing, numerical simulations, and machine learning. In recent years, optical analog approaches have demonstrated higher computing performance and better power efficiency than their digital counterparts. However, analog computing chips usually need large areas and complex structures for parallel computing, as a single device element only executes one computing operation at a single time. Here, we demonstrate frequency-domain computing using the nonlinear acoustic-wave devices on lithium niobate, featuring a normalized external second-harmonic generation conversion efficiency of ~ 5.7 × 10-4 W-1. The second-order sum-frequency nonlinear process of lithium niobate enables multiplication of inputs encoded in the frequency domain. Compared to the analog schemes, our device features a notably simpler design, and nanofabrication requires only one lift-off. Using a single acoustic-wave device within an area of 0.03 mm2, we can simultaneously conduct over 130,000 multiply-accumulation operations. Our acoustic-wave device shows applications in real and complex vector convolutions and image processing. This demonstration sets the stage for experimental realizations into frequency-domain integrated nonlinear acoustic computing systems, potentially shaping future developments in acoustic neural networks and quantum computing.

chai, mingzhao (ORCID:0009000466226341)↗
DOE OSTI2025

Parallel derivative-free optimization for simulation-based design of behind-the-meter energy systems

In this work, the integrated design and dispatch of behind-the-meter or distributed resources (e.g. stationary battery storage and solar PV generation) is considered. A simulation-based framework is employed, generating high-fidelity results with closed-loop predictive control at a fine resolution, at the expense of high computational cost (several minutes to a few hours per design point). To address this challenge, parallel derivative-free design methods are considered. Four methods are compared, including state-of-the-art surrogate-based methods (Radial-Basis Functions and Gaussian processes) and sampling strategies, an evolutionary-based method, and a simple sequential grid refinement method. As a case study, two types of design problem with increasing complexity are considered, namely, the design of behind-the-meter resources (three design variables) and the inclusion of grid capacity (four design variables). The second yields a constrained design problem for which violations can only be determined after solving the computationally expensive simulation. For the three-dimensional case, all methods present a good performance, achieving a solution within 1% of the optimum after the first iteration, with the sequential grid refinement exhibiting the fastest convergence and achieving the best final objective value. This indicates that the parallel evaluation of multiple sampling points may be more important than the choice of method for small decision spaces. For the four-dimensional constrained case, the Genetic Algorithm presents the best tradeoff between performance and computational effort, while the rough objective function terrain generated by constraint violation penalties reduces the performance of surrogate-based methods. Contour plots with flat regions indicate flexibility in the optimal design and highlight the importance of characterizing the solution space.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Enabling Recycling of Composites: Understanding the Impacts of Multiple Thermal Processing Cycles

When considering the utilization of recycled short carbon fiber feedstock materials for advanced manufacturing, understanding the material degradation behavior is essential in determining how many times a composite material can be effectively reprocessed and remanufactured. This study characterizes the degradation behavior of short carbon fiber acrylonitrile butadiene (CF-ABS) that has been reprocessed five times with twin screw extrusion. Parallel plate rheology was completed to observe the degradation in complex viscosity of the recycled feedstock materials. Gel permeation chromatography (GPC) was utilized to characterize the changes in molecular weight distribution of the recycled materials as a result of thermal and mechanical degradation during the re-processing steps. Rheological characterization, GPC, and twin-screw processing data help inform the process optimizations required to process the recycled feedstock material. Successful characterization of the degradation behavior of short fiber composite feedstock materials aids in increased understanding of the lifespan of high value carbon fiber composite materials and aids in process optimization of recycled composite materials.

Walker, Roo↗