Search NASA⌕ Search

SEARCH · Search NASA

Results for “Generations”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Electronic heat generation in semiconductors: Non-equilibrium excitation and evolution of zone-edge phonons via electron–phonon scattering in photo-excited germanium

We investigate experimentally and using first-principles theory the generation of phonons and the relaxation of carriers on picosecond timescales across the Brillouin zone of photo-excited Ge by inter-valley electron–phonon scattering. The phonons generated are typical of those generated in semiconductor devices, contributing to the accumulation of heat within the material. We simulate the time-evolution of phonon populations, based on first-principles band structure and electron–phonon and phonon–phonon matrix elements, and compare them to data from time-resolved x-ray diffuse scattering experiments, performed at the Linac Coherent Light Source x-ray free-electron laser facility, following photo-excitation by a 50 fs near-infrared optical pulse. We show that the intensity of the non-thermal x-ray diffuse scattering signal, which is observed to grow substantially near the L-point of the Brillouin zone over 3–5 ps, is due to phonons generated by scattering of carriers between the Δ and L valleys. These phonons have low group velocities, resulting in a heat bottleneck. With the inclusion of phonon decay through 3-phonon processes, the simulations also account for other non-thermal features observed in the x-ray diffuse scattering intensity, which are due to anharmonic phonon–phonon scattering of the phonons initially generated by electron–phonon scattering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Impact of mechanical tolerances on partial turn skipping in helical flux compression generator

Maintaining tight mechanical tolerances of the components used in helical flux compression generators is crucial for optimizing device performance. Moving beyond current literature, which provides various approximations for acceptable tolerances, a 3D simulation of the armature stator interaction during generator operation was developed, revealing that existing equations frequently misestimate the tolerance limits. Without restricting the generality of the presented approach, the focus was primarily on the armature’s concentricity and roundness, comparing the acceptable tolerance limits between generators of different sizes. An analytical approach for select geometries was developed, confirming the 3D results. Quantitative results reveal that a steeper Gurney angle and increased winding pitch allow for less restrictive tolerances for eccentricity and ellipticity. Even small deviations from the ideal armature positioning and shape will result in fluctuations of the output current time-derivative, observed experimentally and in simulation. Larger deviations then cause partial turn skipping, associated with loss of magnetic flux. The simulation elucidates the impact of tolerance deviations on generator performance by offering precise tolerance ranges for various generator sizes, thereby facilitating informed design decisions.

42 ENGINEERING↗
DOE OSTI2026

A tutorial on high-order harmonic generation in atoms, molecules, and condensed matter

This tutorial introduces strong-field-driven high-order harmonics, their experimental generation and characterization techniques, and their main applications including attosecond pulse generation and ultrafast spectroscopy of the target material. We begin from the use of atomic targets, where the first high-order harmonic generation (HHG) experiments were realized in the late 1980s. Then, we briefly discuss the basics of the microscopic generation mechanism and how various steps of the mechanism were exploited in applications such as generating isolated attosecond pulses and probing molecular orbitals. We introduce and describe the standard experimental approaches for condensed phase HHG, where we discuss unique technical challenges of the use of solid-state materials, such as the mitigation of plasma formation and laser damage. We cover the fundamentals of high-harmonic spectroscopy in condensed matter systems, such as wide bandgap dielectrics, semiconductors, liquid media, and 2D-crystals. We provide some examples of rapidly emerging spectroscopic capabilities, such as for probing crystal symmetries, Berry phases, and associated non-trivial topological properties of the source material. Finally, we provide an overview of the research field, including some of the challenges, opportunities, and open questions.

Attosecond pulses↗
DOE OSTI2019

Preparing for the Next Generation of EUV Lithography at the Center for X-ray Optics

The introduction of EUV lithography into high-volume semiconductor manufacturing this year represents a monumental milestone for EUV technology. After nearly 30 years of development, the EUV research community has overcome many of the key obstacles required to enable the long-awaited integration of EUV lithography into the lab. These obstacles have included: the development of a stable, high-powered EUV source to ensure adequate exposure tool reliability; controlling EUV mask defects and mask contamination; and the development of EUV resists with adequate sensitivity, resolution, and line width roughness to meet the tolerances required for high-volume manufacturing. As EUV moves into its second generation, there will be new challenges facing the community as it works to push EUV technology into the future. Smaller feature sizes will be achieved using higher numerical aperture optics, which are planned to have an anamorphic geometry (asymmetric magnification and numerical aperture between horizontal and vertical axes) to overcome 3D effects at the mask. This new geometry and its larger angle ranges make understanding mask absorber and multilayer effects all the more important. New methods for high-NA wavefront metrology need to be tested to ensure that these optical systems can be aligned to operate with minimal aberrations. Mask defects need to continue to be studied, and the inclusion of EUV pellicles in the roadmap requires that mask inspection and review systems adapt accordingly. Finally, new resists must be developed to support the increased resolution of feature sizes below 8 nm half pitch. The Center for X-ray Optics (CXRO) at Berkeley Lab has been a leader in EUV research for the past 25 years. Leveraging 13.5 nm EUV light from the Advanced Light Source synchrotron facility, CXRO is home to several EUV and soft X-ray (SXR) research tools that have provided important insights into EUV resists, masks, and coatings. The 0.3 NA Microfield exposure tool (MET) and Dose Calibration Tool (DCT) have played an instrumental role in the development of the current generation of high-resolution EUV resists. The Actinic Inspection Tool (AIT) and its successor, SHARP, have enabled aerial image analysis, providing key insights into mask defects, 3D mask effects, illumination, and aberrations. And the CXRO Reflectometer continues to be the industry standard in multilayer coating and EUV mask scattering metrology. To address the new challenges facing the next generation of EUV lithography, CXRO has upgraded its suite of EUV research tools. The 0.5 NA MET5 is a newly commissioned projection lithography tool that is capable of printing feature sizes down to 8 nm half pitch. A new radiation chemistry program is deploying several techniques aimed at dissecting the role of primary photoelectrons and secondary electrons in EUV resists. The SHARP microscope has been outfitted with anamorphic zone plate lenses that can emulate the geometry of next-generation EUV scanners, and the reflectometer has been applied to new scattering experiments for the purpose of understanding the 3D effects of EUV mask multilayers, as well as determining mask properties using scattering profiles. In parallel with these tools, the CXRO High-NA Wavefront Sensing Program is developing high-resolution wavefront sensors suitable for measuring aberrations at high NA. This article presents an overview of these programs and describes how they will address the primary challenges that face the EUV community as it moves to the next generation of EUV lithography.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

The ICRP, MELODI, and ALLIANCE workshop on effects of ionizing radiation exposure in offspring and next generations: a summary of discussions

Task Group 121 – Effects of ionizing radiation exposure in offspring and next generations – is a task group under the Committee 1 of the International Commission on Radiological Protection (ICRP), approved by the Main Commission on 18th November 2021. The main goals of Task Group 121 are to (1) review and update the scientific literature of relevance to radiation-related effects in the offspring of parent(s) exposed to ionizing radiation in both human and non-human biota; (2) to assess preconceptional and intrauterine effects of radiation exposure and related morbidity and mortality; and, (3) to provide advice about the level of evidence and how to consider these preconceptional and postconceptional effects in the system of radiological protection for humans and non-human biota. The Task Group is reviewing relevant literature since Publication 90 ‘Biological effects after prenatal irradiation (embryo and fetus)’ (2003) and will include radiation-related effects on future generations in humans, animals, and plants. This review will be conducted to account for the health effects on offspring and subsequent generations in the current system of radiological protection. Radiation detriment calculation will also be reviewed. Finally, preliminary recommendations will be made to update the integration of health effects in offspring and next generations in the system of radiological protection. A Workshop, jointly organized by ICRP Task Group 121 and European Radiation Protection Research Platforms MELODI and ALLIANCE was held in Budapest, Hungary, from 31st May to 2nd June 2022. Participants discussed four important topics: (1) hereditary and epigenetic effects due to exposure of the germ cell line (preconceptional exposure), (2) effects arising from exposure of the embryo and fetus (intrauterine exposure), (3) transgenerational effects on biota, and (4) its potential impact on the system of radiological protection. Based on the discussions and presentations during the breakout sessions, newer publications, and gaps on the current scientific literature were identified. For instance, there are some ongoing systematic reviews and radiation epidemiology reviews of intrauterine effects. There are newer methods of Monte Carlo simulation for fetal dosimetry, and advances in radiation genetics, epigenetics, and radiobiology studies. While the current impact of hereditary effects on the global detriment was reported as small, the questions surrounding the effects of radiation exposure on offspring and the next generation are crucial, recurring, and with a major focus on exposed populations. Here, this article summarizes the workshop discussions, presentations, and conclusions of each topic and introduces the special issue of the International Journal of Radiation Biology resulting from the discussions of the meeting.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2017

Event generator tuning using Bayesian optimization

Monte Carlo event generators contain a large number of parameters that must be determined by comparing the output of the generator with experimental data. Generating enough events with a fixed set of parameter values to enable making such a comparison is extremely CPU intensive, which prohibits performing a simple brute-force grid-based tuning of the parameters. Bayesian optimization is a powerful method designed for such black-box tuning applications. In this article, we show that Monte Carlo event generator parameters can be accurately obtained using Bayesian optimization and minimal expert-level physics knowledge. A tune of the PYTHIA 8 event generator using $e^+e^-$ events, where 20 parameters are optimized, can be run on a modern laptop in just two days. Combining the Bayesian optimization approach with expert knowledge should enable producing better tunes in the future, by making it faster and easier to study discrepancies between Monte Carlo and experimental data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Generative Thermodynamic Computing

Here, we introduce a generative modeling framework for thermodynamic computing, in which structured data are synthesized from noise by the natural time evolution of a physical system governed by Langevin dynamics. While conventional diffusion models use neural networks to perform denoising, here the information needed to generate structure from noise is encoded by the dynamics of a thermodynamic system. Training proceeds by maximizing the probability with which the computer generates the reverse of a noising trajectory, which ensures that the computer generates data with minimal heat emission. We demonstrate this framework within a digital simulation of a thermodynamic computer. If realized in analog hardware, such a system would function as a generative model that produces structured samples without the need for artificially injected noise or active control of denoising.

Whitelam, Stephen [Lawrence Berkeley National Labo↗
DOE OSTI2018

Power Generation from a Radiative Thermal Source Using a Large-Area Infrared Rectenna

Electrical power generation from a moderate-temperature thermal source by means of direct conversion of infrared radiation is important and highly desirable for energy harvesting from waste heat and micropower applications. Here, we demonstrate direct rectified power generation from an unbiased large-area nanoantenna-coupled tunnel diode rectifier called a rectenna. Using a vacuum radiometric measurement technique with irradiation from a temperature-stabilized thermal source, a generated power density of 8 nW / cm 2 is observed at a source temperature of 450°C for the unbiased rectenna across an optimized load resistance. The optimized load resistance for the peak power generation for each temperature coincides with the tunnel diode resistance at zero bias and corresponds to the impedance matching condition for a rectifying antenna. Current-voltage measurements of a thermally illuminated large-area rectenna show current zero crossing shifts into the second quadrant indicating rectification. Photon-assisted tunneling in the unbiased rectenna is modeled as the mechanism for the large short-circuit photocurrents observed where the photon energy serves as an effective bias across the tunnel junction. Furthermore, the measured current and voltage across the load resistor as a function of the thermal source temperature represents direct current electrical power generation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Neutrinoless double-β decay of 124 Sn, 130 Te, and 136 Xe in the Hamiltonian-based generator-coordinate method

We present a generator-coordinate method for realistic shell-model Hamiltonians that closely approximates the full shell model calculations of the matrix elements for the neutrinoless double-β decay of 124 Sn, 130 Te, and 136 Xe. Here, we treat not only quadrupole deformations but also the proton-neutron pairing amplitudes as generator coordinates. We validate this method by calculating and comparing spectroscopic quantities with the exact shell model results and experimental data. Our Hamiltonian-based generator-coordinate method produces 0νββ matrix elements much closer to the shell model ones, compared to the existing energy-density-functional-based generator-coordinate approaches. The remaining overestimation of 0νββ nuclear matrix element suggests that additional correlations may be needed to be taken into account for 124 Sn, 130 Te, and 136 Xe when calculating with the Hamiltonian-based generator-coordinate method. The validation of this method may open the possibility of calculating 0νββ matrix element of 150 Nd in a large shell-model space.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Driving Next-Generation Workflows from the Data Plane

We observe the emergence of a new generation of scientific workflows that process data produced at a sustained rate by scientific instruments and large scale numerical simulations. This data is consumed by multiple analysis, visualization, or Machine Learning components not only to enable inference and justify the scientific program, but also to monitor and steer the evolution of these experiments. In such workflows, moving intermediate data efficiently is key to performance, more than efficiently scheduling computational tasks. However, most traditional workflow management systems focus on optimizing task scheduling and then deal with data management, assuming a “move little, compute for long” model, which makes them unfit to the efficient management of this new generation of workflows. Therefore, we advocate for a new way to manage scientific workflows. We propose to consider an efficiently and independently managed data plane that can store and stream data. Workflows compute components, in the application plane can then interact with the data plane, abstracted from complexities of data management. Then, the role of a workflow management system would become that of a control plane that allows users to connect services together to execute the workflow and manages connections between the application and data planes. In this position paper, we characterize several next-generation workflow motifs and describe how their interaction with the data plane is a challenge to traditional workflow management systems. Then, we express a set of requirements that a workflow management system should meet to efficiently manage next-generation workflows at different scales. Based on these requirements, we expose our vision of driving next-generation workflows from the data plane and list remaining open challenges.

Suter, Fred↗
DOE OSTI2019

Local Feature Sufficiency Exploration for Predicting Security-constrained Generation Dispatch in Multi-Area Power Systems

Deriving generation dispatch is essential for efficient and secure operation of electric power systems. This is usually achieved by solving a security-constrained optimal power flow(SCOPF) problem, which is by nature non-convex, nonlinear and thus computational intensive. The state-of-the-art optimization approaches are not able to solve this problem for large-scale power systems within power system operation time window (usually 5 minutes). In this work, we developed supervised learning approaches to determine security-constrained generation dispatch within much shorter time window. More importantly, the physical constrain of only accessing to local measurements and other information in most utilities’ real-time operation can not be ignored for the predictive models.The feasibility and accuracy of utilizing only local features(measurements and grid information in one area) to predict optimal local generation dispatch (dispatch of all generators in the corresponding area) in multi-area power systems has been explored. The results showed optimal local generation dispatch can be predicted with local features with high accuracy, which is comparable to the results obtained with global features.

Sun, Yixuan↗
DOE OSTI2017

Development of a 100 kV pulse generator for driving an electron scanner used in proton beam profile measurements

The Spallation Neutron Source (SNS) utilizes an electron scanner in the accumulator ring for nondestructive transverse profiling of the proton beam. The electron scanner consists of a high voltage pulse generator driving an electron gun, a medium voltage ramp generator, and a CCD camera. A new high voltage pulse generator that provides negative 100 kV pulses with rise times of less than 200 ns, +/-0.5% flattop of greater than 100 ns has been designed, delivered, and undergone extensive testing. The pulse generator has been operationally verified with the existing control system and simulated loads. Full system testing with the actual electron scanner is planned. This paper details the requirements, design, setup, and test results of the high voltage pulse generator.

Morris, B↗
DOE OSTI2024

ChatBLAS: The First AI-Generated and Portable BLAS Library

We present ChatBLAS, the first AI-generated and portable Basic Linear Algebra Subprograms (BLAS) library on different CPU/GPU configurations. The purpose of this study is (i) to evaluate the capabilities of current large language models (LLMs) to generate a portable and HPC library for BLAS operations and (ii) to define the fundamental practices and criteria to interact with LLMs for HPC targets to elevate the trustworthiness and performance levels of the AI-generated HPC codes. The generated C/C++ codes must be highly optimized using device-specific solutions to reach high levels of performance. Additionally, these codes are very algorithm-dependent, thereby adding an extra dimension of complexity to this study. We used OpenAI’s LLM ChatGPT and focused on vector-vector BLAS level-1 operations. ChatBLAS can generate functional and correct codes, achieving high-trustworthiness levels, and can compete or even provide better performance against vendor libraries.

Valero Lara, Pedro↗
DOE OSTI2017

Generation Expansion Planning With Large Amounts of Wind Power via Decision-Dependent Stochastic Programming

Power generation expansion planning needs to deal with future uncertainties carefully, given that the invested generation assets will be in operation for a long time. Many stochastic programming models have been proposed to tackle this challenge. However, most previous works assume predetermined future uncertainties (i.e., fixed random outcomes with given probabilities). In several recent studies of generation assets' planning (e.g., thermal versus renewable), new findings show that the investment decisions could affect the future uncertainties as well. To this end, this paper proposes a multistage decision-dependent stochastic optimization model for long-term large-scale generation expansion planning, where large amounts of wind power are involved. In the decision-dependent model, the future uncertainties are not only affecting but also affected by the current decisions. In particular, the probability distribution function is determined by not only input parameters but also decision variables. To deal with the nonlinear constraints in our model, a quasi-exact solution approach is then introduced to reformulate the multistage stochastic investment model to a mixed-integer linear programming model. The wind penetration, investment decisions, and the optimality of the decision-dependent model are evaluated in a series of multistage case studies. The results show that the proposed decision-dependent model provides effective optimization solutions for long-term generation expansion planning.

Zhan, Yiduo↗
DOE OSTI2022

Generative Design for Resilience of Interdependent Network Systems

Abstract Interconnected complex systems usually undergo disruptions due to internal uncertainties and external negative impacts such as those caused by harsh operating environments or regional natural disaster events. To maintain the operation of interconnected network systems under both internal and external challenges, design for resilience research has been conducted from both enhancing the reliability of the system through better designs and improving the failure recovery capabilities. As for enhancing the designs, challenges have arisen for designing a robust system due to the increasing scale of modern systems and the complicated underlying physical constraints. To tackle these challenges and design a resilient system efficiently, this study presents a generative design method that utilizes graph learning algorithms. The generative design framework contains a performance estimator and a candidate design generator. The generator can intelligently mine good properties from existing systems and output new designs that meet predefined performance criteria while the estimator can efficiently predict the performance of the generated design for a fast iterative learning process. Case studies results based on synthetic supply chain networks and power systems from the IEEE dataset have illustrated the applicability of the developed method for designing resilient interdependent network systems.

Engineering↗
DOE OSTI2018

ACOUSTIC PRESSURE FIELDS GENERATED WITH A HIGH FREQUENCY ACOUSTIC LEVITATOR

Acoustic levitation is an advantageous particle positioning mechanism currently employed for applications of x-ray spectroscopy and micro-material manufacturing[1], [2]. By levitating a particle using only acoustic pressure waves, one eliminates the need for a container or other physical structure which may contaminate the specimen. Unfortunately, the pressure field generated by a standing acoustic wave is susceptible to periodic instabilities, and a particle that is levitated in this field tends to vibrate. The amplitude of the vibration is largest in the directions that are orthogonal to the axis in which the acoustic wave is generated. Therefore, by generating additional acoustic waves in each orthogonal axis, the vibration amplitude of the levitated particle is significantly reduced. The authors have shown this phenomenon to be true in a previous study[3]. In this paper, the authors explore the details of the pressure field that is generated with the device. A single degree-of freedom relationship is developed between the acoustic field pressure, the location of the levitated particle, and the mechanical vibration needed to produce levitation. In order to levitate a 100 micrometer diameter water droplet at 55 kilohertz, the calculations suggest that the transducer must achieve an average surface vibration amplitude of at least 6.43 micrometers. This mechanical vibration must produce a root means-squared pressure amplitude of 933 Pascal. Under these conditions, the particle will levitate approximately 0.4 millimeters below a zero pressure node. To validate the use of the single degree of freedom relationships and to explore the acoustic field for one, two, and three-axis levitation, the authors designed and prototyped an acoustic levitator capable of generating standing waves in three orthogonal directions. Using a simple electrical control circuit, the acoustic wave transducers of each axis can be turned on individually or simultaneously. An experiment was developed to measure the pressure of the acoustic field using a microphone. Preliminary pressure magnitude results were measured for one axis levitation along the center of the vertical axis of the levitator. The measurements suggest that the theoretical development provides a valid first approximation for the pressure magnitude and required mechanical vibration amplitude.

acoustic levitator↗
DOE OSTI2024

Generative models for simulation of KamLAND-Zen

Abstract The next generation of searches for neutrinoless double beta decay ($$0 \nu \beta \beta $$ 0 ν β β ) are poised to answer deep questions on the nature of neutrinos and the source of the Universe’s matter–antimatter asymmetry. They will be looking for event rates of less than one event per ton of instrumented isotope per year. To claim discovery, accurate and efficient simulations of detector events that mimic$$0 \nu \beta \beta $$ 0 ν β β is critical. Traditional Monte Carlo (MC) simulations can be supplemented by machine-learning-based generative models. This work describes the performance of generative models that we designed for monolithic liquid scintillator detectors like KamLAND to produce accurate simulation data without a predefined physics model. We present their current ability to recover low-level features and perform interpolation. In the future, the results of these generative models can be used to improve event classification and background rejection by providing high-quality abundant generated data.

Physics↗
DOE OSTI2020

Generating Massive Scale-free Networks: Novel Parallel Algorithms using the Preferential Attachment Model

Recently, there has been substantial interest in the study of various random networks as mathematical models of complex systems. As real-life complex systems grow larger, the ability to generate progressively large random networks becomes all the more important. This motivates the need for efficient parallel algorithms for generating such networks. Naïve parallelization of sequential algorithms for generating random networks is inefficient due to inherent dependencies among the edges and the possibility of creating duplicate (parallel) edges. In this article, we present message passing interface-based distributed memory parallel algorithms for generating random scale-free networks using the preferential-attachment model. Our algorithms are experimentally verified to scale very well to a large number of processing elements (PEs), providing near-linear speedups. The algorithms have been exercised with regard to scale and speed to generate scale-free networks with one trillion edges in 6 minutes using 1,000 PEs.

97 MATHEMATICS AND COMPUTING↗