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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Security vulnerabilities of connected vehicle streams and their impact on cooperative driving

Autonomous vehicles capable of navigating unpredictable real-world environments with little human feedback are a reality today. Such systems rely heavily on onboard sensors such as cameras, radar/LIDAR, and GPS as well as capabilities such as 3G/4G connectivity and V2V/V2I communication to make real-time maneuvering decisions. Autonomous vehicle control imposes very strict requirements on the security of the communication channels used by the vehicle to exchange information as well as the control logic that performs complex driving tasks such as adapting vehicle velocity or changing lanes. This research presents a first look at the effects of security attacks on the communication channel as well as sensor tampering of a connected vehicle stream equipped to achieve CACC. Our simulation results show that an insider attack can cause significant instability in the CACC vehicle stream. We also outline how different countermeasures, such as downgrading to ACC mode, could potentially be used to improve the security and safety of the connected vehicle streams.

42 ENGINEERING↗
DOE OSTI2023

Frontiers in the Application of RF Vacuum Electronics

The application of radio frequency (RF) vacuum electronics for the betterment of the human condition began soon after the invention of the first vacuum tubes in the 1920s and has not stopped since. Today, microwave vacuum devices are powering important applications in health treatment, material and biological science, wireless communication-terrestrial and space, Earth environment remote sensing, and the promise of safe, reliable, and inexhaustible energy. This article highlights some of the exciting application frontiers of vacuum electronics.

42 ENGINEERING↗
DOE OSTI2021

AN AUTOMATED MACHINE LEARNING-GENETIC ALGORITHM FRAMEWORK WITH ACTIVE LEARNING FOR DESIGN OPTIMIZATION

The use of machine learning (ML)-based surrogate models is a promising technique to significantly accelerate simulation-driven design optimization of internal combustion (IC) engines, due to the high computational cost of running computational fluid dynamics (CFD) simulations. However, training the ML models requires hyperparameter selection, which is often done using trial-and-error and domain expertise. Another challenge is that the data required to train these models are often unknown a priori. In this work, we present an automated hyperparameter selection technique coupled with an active learning approach to address these challenges. The technique presented in this study involves the use of a Bayesian approach to optimize the hyperparameters of the base learners that make up a super learner model. In addition to performing hyperparameter optimization (HPO), an active learning approach is employed, where the process of data generation using simulations, ML training, and surrogate optimization is performed repeatedly to refine the solution in the vicinity of the predicted optimum. The proposed approach is applied to the optimization of a compression ignition engine with control parameters relating to fuel injection, in-cylinder flow, and thermodynamic conditions. It is demonstrated that by automatically selecting the best values of the hyperparameters, a 1.6% improvement in merit value is obtained, compared to an improvement of 1.0% with default hyperparameters. Overall, the framework introduced in this study reduces the need for technical expertise in training ML models for optimization while also reducing the number of simulations needed for performing surrogate-based design optimization.

Owoyele, Opeoluwa↗
DOE OSTI2017

Electroless Deposition of Palladium on Macroscopic 3D-Printed Polymers with Dense Microlattice Architectures for Development of Multifunctional Composite Materials

A simple procedure has been developed to create palladium (Pd) films on the surface of several common polymers used in commercial fused deposition modeling (FDM) and stereolithography (SLA) based three-dimensional (3D) printing by an electroless deposition process. The procedure can be performed at room temperature, with equipment less expensive than many 3D printers, and occurs rapidly enough to achieve full coverage of the film within a few minutes. 3D substrates composed of dense logpile or cubic lattices with part sizes in the mm to cm range, and feature sizes as small as 150 μm were designed and printed using commercially available 3D printers. The deposition procedure was successfully adapted to show full coverage in the lattice substrates. As a result, the ability to design, print, and metallize highly ordered three-dimensional microscale structures could accelerate development of a range of optimized chemical and mechanical engineering systems.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Multiphase Nano-Composite Coatings for Achieving Energy Optimization

UES Inc. and ANL teamed in this work to develop novel coating systems for the protection of surfaces from thermal degradation mainly in two applications; Machining and Die casting. These coatings were specifically designed for the purpose by incorporating required material phases and the overall architecture, which led to reduce the energy usage and increase efficiency of the operations. Following the UES/ANL's feasibility work, the coatings were developed utilizing High power impulse magnetron sputtering (HiPMS) and Large area filtered arc deposition (LAFAD) techniques. Toughness, hardness and oxidation resistance: contrasting qualities have been mixed in the right proportion to attain the suitable material characteristic for the cause. Hafnium diboride (HfB 2 ) based materials provided such a system and its properties were tamed to attain the right combination of toughness and hardness by working on the microstructure and architecture of coatings. An effective interfacing material (graded concentrations of topcoat) was also achieved in this work to provide the required adhesion between the substrate and the coating. Combination of an appropriate bond coat and a functional top coat provided the present thermal degradation resistant coating for cutting tools and die-casting applications. Laboratory level performance tests and industrial level application tests by partner companies (Beta Site Testing) were used for the development of these coatings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Production Target Design Report

The Northstar 99 Mo production target, a cylindrical length of 100 Mo rod, has evolved considerably since its first conception. The cylinder was very early sliced into disks to increase the heat transfer area, first to 1 mm thick disks then to the current 0.5 mm thick. The coolant was changed early in the target development from water to helium to eliminate corrosion and dissolution. The diameter has increased from initially 6 mm to 12 mm, the current diameter of the test target now at ANL, to nominally 28 mm (26-30.6 mm, depending upon optimal beam spot size and shape). The length has also changed to improve the production to cost ratio, so now the target is nominally 41 mm long (excluding coolant gaps between disks), and irradiated on both ends. This report summarizes the current status of the plant target design.

Accelerator Design, Technology, and Operations↗
DOE OSTI2020

The Dark Energy Spectrographic Instrument (DESI) Corrector Assembly

The specific research of the DESI project is to study in detail the expansion history of the Universe over the past 10 billion years. In order to do this, the project designed, fabricated, tested and commissioned the DESI instrument which has been deployed at the Mayall Telescope at the Kitt Peak National Observatory near Tucson, Arizona. The DESI project was conducted by approximately 30 US and foreign national laboratories. Our CRADA with University College London (UCL) involved both research planning for eventual observing on the DESI telescope; and in the build of the optical corrector, a major part of the instrument. The key major goals of this CRADA were achieved. For survey planning, Drs. Lahav, Abdalla, Peiris, Pontzen and Dr. Farihi were all important contributors to the working groups to which they were assigned. Their modelling efforts, cosmological simulations, target selection and analyses of imaging surveys have been vital in the early planning for targets during commissioning. The major role UCL played in the development of the instrument was performed by Drs. Doel and Brooks. The optical corrector components were developed by scientists and engineers at Lawrence Berkeley National Laboratory and at Fermi National Accelerator Laboratory. UCL was assigned the arduous responsibility for creating the instrumentation necessary to take all the separate components (lenses, cells, rings) and incorporate them, while precisely aligning the optics. Following that, they installed the corrector inside the barrel and shipped everything to the Mayall. It was a great success that the optical barrel arrived safely in good condition. Drs. Doel and Brooks were involved in every step of the fabrication and kept in constant contact with the LBNL DESI Project Manager and Project Director. They were extremely successful in their alignment, which was proved by early observations. First light on the telescope was achieved on October 22, 2020. The first spectrum was taken of a random star at zenith. Shortly thereafter, the telescope slewed to M33 and several spectra were taken there and later in the Persus nebula. It was a major accomplishment for the project.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Hybrid physics-based and machine learning tools for materials assessment

In this work, we develop novel physics-based and machine learning computational techniques to predict fundamental properties of metallic systems that affect radiation damage behavior in reactor structural materials. Oftentimes, atomistic predictions of engineering alloys simplify chemical compositions to a single element to reduce computational cost and complexity, introducing large sources of uncertainty and potentially missing important behavior. In addition, engineering alloys such as SS 316 are particularly challenging to simulate with first principles methods because of the additional degrees of freedom introduced by magnetic natures of the constituent elements, and very little data of this type exists within the literature. These novel methods aim to improve the qualitative prediction of radiation damage in engineering alloys by more accurately simulating their compositions, both by accelerating the computations and by developing novel analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

CIE Curriculum Guide (V.2.0)

The Cyber-Informed Engineering (CIE) Curriculum Guide offers a comprehensive framework, guidance, and resources for integrating CIE into university-level engineering programs and related educational activities. The primary goal is to help educators adopt CIE principles into their teaching to produce future engineers and technicians who understand digital risks in modern engineered systems, thereby addressing the nation’s infrastructure resilience needs. This guide outlines practical integration examples, links to resources to accelerate CIE adoption, and shares insights from partner academic institutions on various implementation strategies. CIE is a framework for embedding engineered controls that mitigate the impact of cyber-attacks in any cyber-physical system used in critical energy infrastructure and other sectors. Developed by the U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER), the National Cyber-Informed Engineering Strategy emphasizes embedding CIE into formal education, training, and credentialing. This guide supports this strategic objective by providing examples of integrating CIE concepts into engineering curricula, from class activities to new courses and certificate programs. The importance of educating cyber-informed engineers is underscored by the evolving cybersecurity threats facing engineered systems. As industrial control systems (ICS) increasingly incorporate digital technologies, the responsibility for security extends to both cyber professionals and engineers. CIE addresses critical gaps in designing and protecting physical systems with digital components against cyber risks, ensuring engineers consider digital risk throughout the engineering design lifecycle. Currently, engineering education does not routinely include cyber-informed principles, highlighting a gap in addressing modern engineering system risks. This guide advocates for updating engineering curricula to include digital risk management as a fundamental element. By doing so, future engineers will be equipped to design resilient systems that mitigate digital risks from the outset. Through this guide, engineering faculty can integrate CIE into their curricula, bridging the gap between digital risk and engineering. This approach prepares a cyber-informed workforce capable of safeguarding the cyber-physical systems crucial to national security and public welfare. By embedding CIE into education and training, institutions can produce engineers and technicians who can effectively mitigate cyber impacts throughout the engineering design lifecycle, resulting in more secure critical infrastructures.

42 - ENGINEERING↗
DOE OSTI2013

ESS Presentation

Abstract Not Provided

Accelerator Design, Technology, and Operations↗
DOE OSTI2022

Feature engineering for machine learning enabled early prediction of battery lifetime

Accurate battery lifetime estimates enable accelerated design of novel battery materials and determination of optimal use protocols for longevity in deployments. Unfortunately, traditional battery testing may take years to reach thousands of cycles. Recent studies have shown that machine learning (ML) tools can predict lithium-ion battery lifetimes from 100 or fewer preliminary cycles, representing only a few weeks of cycling. Until now, conclusions about the efficacy and broad applicability of these predictions across a variety of cathode chemistries have been limited by available experimental information. In this work, we leverage a battery cycling dataset representing six cathode chemistries (NMC111, NMC532, NMC622, NMC811, HE5050, and 5Vspinel), multiple electrolyte/anode compositions, and 300 total carefully prepared pouch batteries to explore feature selection and battery chemistry's role in ML battery lifetime predictions. Here, a mean absolute error (MAE) of 78 cycles in prediction was seen for a chemistry-spanning test set from 100 preliminary cycles. Furthermore, an MAE of 103 cycles was seen when using only the first cycle. This study represents an in-depth investigation of strategies for feature selection for battery lifetime prediction, ML models' generalization across multiple battery chemistries, and predictions beyond the training set in the chemical space.

25 ENERGY STORAGE↗
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 OSTI2026

Advances in genetic tools for metabolic engineering of non-conventional yeasts

Non-conventional yeasts are emerging as powerful alternatives to Saccharomyces cerevisiae for metabolic engineering, owing to their innate stress tolerance, broad substrate utilization, and distinctive metabolic capabilities. These attributes position them as promising chassis for producing biofuels, pharmaceuticals, and specialty chemicals. This review synthesizes recent advances in genetic toolkits for four such species—Pichia kudriavzevii (Issatchenkia orientalis), Starmerella bombicola, Debaryomyces hansenii, and Pachysolen tannophilus—highlighting progress across plasmid architectures (episomal and integrative), identification of autonomously replicating sequences and centromeric elements, and the development of safe-harbor genomic loci. We summarize promoter and terminator libraries enabling tunable expression, the expansion of auxotrophic and antifungal selection markers with recycling strategies, and the rapid adaptation of CRISPR-based systems (Cas9 and Cas12a) with optimized guide RNA expression, multiplex editing, and approaches that enhance homologous recombination (e.g., KU70/80 disruption). We also review landing-pad platforms for modular, repeated integrations and transposon-based tools (e.g., piggyBac) that facilitate multigene pathway assembly. Collectively, these innovations are accelerating design-build-test-learn cycles and enabling precise, scalable engineering of non-conventional yeasts. Remaining challenges—including limited species-specific episomal systems, variable transformation efficiencies, genome-stability concerns, and alternative codon usage—define clear priorities for future toolkit development. Together, these advances and open needs chart a path toward robust, sustainable biomanufacturing using diverse non-conventional yeast chassis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Conformational ensembles reveal the origins of serine protease catalysis

Enzymes exist in ensembles of states that encode the energetics underlying their catalysis. Conformational ensembles built from 1231 structures of 17 serine proteases revealed atomic-level changes across their reaction states. By comparing the enzymatic and solution reaction, we identified molecular features that provide catalysis and quantified their energetic contributions to catalysis. Serine proteases precisely position their reactants in destabilized conformers, creating a downhill energetic gradient that selectively favors the motions required for reaction while limiting off-pathway conformational states. The same catalytic features have repeatedly evolved in proteases and additional enzymes across multiple distinct structural folds. In conclusion, our ensemble-function analyses revealed previously unknown catalytic features, provided quantitative models based on simple physical and chemical principles, and identified motifs recurrent in nature that may inspire enzyme design.

Du, Siyuan [Stanford Univ., CA (United States)] (O↗