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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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31 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Airships as Transformative Tools for Power Systems Logistics: Addressing Infrastructure Challenges and Enhancing Disaster Resilience

Airships represent a transformative advancement in logistics, particularly for the power systems industry. Their unique ability to transport heavy equipment and personnel efficiently over remote or disaster-stricken areas, while requiring minimal infrastructure, addresses critical gaps left by traditional methods. Combining adaptability with environmental sustainability, airships offer a low-carbon alternative for routine operations and emergency responses. This review presents current developments in airship technology, such as rigid airships designed for large payloads, demonstrate their potential to revolutionize supply chains.

Fuhr, Peter L. [ORNL] (ORCID:0000000211627445)↗
DOE OSTI2021

Exploration of multifidelity UQ sampling strategies for computer network applications.

Network modeling is a powerful tool to enable rapid analysis of complex systems that can be challenging to study directly using physical testing. Here, two approaches are considered: emulation and simulation. The former runs real software on virtualized hardware, while the latter mimics the behavior of network components and their interactions in software. Although emulation provides an accurate representation of physical networks, this approach alone cannot guarantee the characterization of the system under realistic operative conditions. Operative conditions for physical networks are often characterized by intrinsic variability (payload size, packet latency, etc.) or a lack of precise knowledge regarding the network configuration (bandwidth, delays, etc.); therefore uncertainty quantification (UQ) strategies should be also employed. UQ strategies require multiple evaluations of the system with a number of evaluation instances that roughly increases with the problem dimensionality, i.e., the number of uncertain parameters. It follows that a typical UQ workflow for network modeling based on emulation can easily become unattainable due to its prohibitive computational cost. In this paper, a multifidelity sampling approach is discussed and applied to network modeling problems. The main idea is to optimally fuse information coming from simulations, which are a low-fidelity version of the emulation problem of interest, in order to decrease the estimator variance. By reducing the estimator variance in a sampling approach it is usually possible to obtain more reliable statistics and therefore a more reliable system characterization. Several network problems of increasing difficulty are presented. For each of them, the performance of the multifidelity estimator is compared with respect to the single fidelity counterpart, namely, Monte Carlo sampling. For all the test problems studied in this work, the multifidelity estimator demonstrated an increased efficiency with respect to MC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Multivariate Flexible Framework with High Usable Hydrogen Capacity in a Reduced Pressure Swing Process

Step-shaped adsorption-desorption of gaseous payloads by flexible metal-organic frameworks can facilitate the delivery of large usable capacities with significantly reduced energetic penalties. This is desirable for the storage, transport, and delivery of H 2 , as prototypical adsorbents require large swings in pressure and temperature to achieve usable capacities approaching their total capacities. However, the weak physisorption of H 2 typically necessitates undesirably high pressures to induce the framework phase change. As de novo design of flexible frameworks is exceedingly challenging, the ability to intuitively adapt known frameworks is required. We demonstrate that the multivariate linker approach is a powerful tool for tuning the phase change behavior of flexible frameworks. In this work, 2-methyl-5,6-difluorobenzimidazolate was solvothermally incorporated into the known framework CdIF-13 (sod-Cd(benzimidazolate) 2 ), resulting in the multivariate framework sod-Cd(benzimidazolate) 1.87 (2-methyl-5,6-difluorobenzimidazolate) 0.13 (ratio = 14:1), which exhibited a considerably reduced stepped adsorption threshold pressure while maintaining the desirable adsorption-desorption profile and capacity of CdIF-13. At 77 K, the multivariate framework exhibits stepped H 2 adsorption with saturation below 50 bar and minimal desorption hysteresis at 5 bar. At 87 K, saturation of step-shaped adsorption occurs by 90 bar, with hysteresis closing at 30 bar. These adsorption-desorption profiles enable usable capacities in a mild pressure swing process above 1 mass %, representing 85-92% of the total capacities. Here this work demonstrates that the desirable performance of flexible frameworks can be readily adapted through the multivariate approach to enable efficient storage and delivery of weakly physisorbing species.

08 HYDROGEN↗
DOE OSTI2024

Exploring Class 8 Long-Haul Truck Electrification: Key Technology Evaluation and Potential Challenges

The phenomena of global warming and climate change are encouraging more and more countries, local communities, and companies to establish carbon neutrality targets, which has very significant implications for the US trucking industry. Truck electrification helps fleets to achieve zero tailpipe emissions and macro-scale decarbonization while allowing continued business growth in response to the rapid expansion of e-commerce and shipping related to increased globalization. Here, this paper presents an analysis of Class 8 long-haul truck electrification using a commercial vehicle electrification evaluation tool and Fleet DNA drive data. The study provides new insight into the impacts of streamlined chassis, battery energy density, and superfast charging on battery capacity needs as well as implications for payload, energy consumption, and greenhouse gas emissions for electric long-haul trucks. The study also identifies a pathway for achieving optimal long-haul truck electrification. The results show that no single technology can simultaneously achieve significant improvements in all these key areas and that a cost-effective approach requires a deliberate combination of all of these technologies. Moreover, the analysis highlights the strong evolution of vehicle and battery technologies and the excellent potential for long-haul truck electrification to achieve 100% year-round service coverage with continued technology advancement.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Achieving Diesel Powertrain Ownership Parity in Battery Electric Heavy Duty Commercial Vehicles Using a Rapid Recurrent Recharging Architecture

Battery electric vehicles (BEV) in heavy duty (HD) commercial freight transport face challenging technoeconomic barriers to adoption. Specifically, beyond safety and compliance, fleet and operational logistics require both high up-time and parity with diesel system productivity/Total Cost of Ownership (TCO) to enable strong adoption of electrified powertrains. At present, relatively high energy storage prices coupled with the increased weight of BEV systems limit the practicality of HD commercial freight transport to shorter range applications, where smaller batteries will suffice for the mission energy requirements (single operational shift). This paper presents an approach to extend the feasibility of BEV HD trucking for a broad range of applications. The concept is based on the leveraging rapid and recurrent recharging of a BEV HD truck that may either already make frequent stops due to shipment drop-offs/reloading or be required to make frequent stops along with longer missions for recharging. While the challenges of the latter are well appreciated, the concept proposed explores making minimal impact to overall mission time by targeting high C-rate charging while optimizing the frequency (miles) through which these events must occur. The concept optimizes battery size and chemistry, such that the expected life (years and total energy throughput) is balanced with the depth of discharge between recharging events, thus making complete use of the energy available through the life of the battery system. The solution is constrained to minimize the impact on payload capacity. The paper analyzes critical levers in achieving diesel price parity (based on a simplified vehicle TCO), achieved through different purchase options (including lease versus buy) and operational models (half-life swap out). Finally, the paper identifies the application design domain where these solutions are viable with limited impact on fleet operations.

Sujan, Vivek↗
DOE OSTI2025

Toward a persistent event-streaming system for high-performance computing applications

High-performance computing (HPC) applications have traditionally relied on parallel file systems and file transfer services to manage data movement and storage. Alternative approaches have been proposed that use direct communications between application components, trading persistence and fault tolerance for speed. Event-driven architectures, as popularized in enterprise contexts, present a compelling middle ground, avoiding the performance cost and API constraints of parallel file systems while retaining persistence and offering impedance matching between application components. However, adapting streaming frameworks to HPC workloads requires addressing challenges unique to HPC systems. This paper investigates the potential for a streaming framework designed for HPC infrastructures and use cases. We introduce Mofka, a persistent event-streaming framework designed specifically for HPC environments. Mofka combines the capabilities of a traditional streaming service with optimizations tailored to the HPC context, such as support for massively multicore nodes, efficient scaling for large producer-consumer workflows, RDMA-enabled high-performance network communications, specialized network fabrics with multiple links per node, and efficient handling of large scientific data payloads. Built using the Mochi suite of HPC data service components, Mofka provides a lightweight, modular, and high-performance solution for persistent streaming in HPC systems. We present the architecture of Mofka and evaluate its performance against Kafka and Redpanda using benchmarks on diverse platforms, including Argonne's Polaris and Oak Ridge's Frontier supercomputers, showing up to 8× improvement in throughput in some scenarios. We then demonstrate its utility in several real-world applications: a tomographic reconstruction pipeline, a workflow for the discovery of metal-organic frameworks for carbon capture, and the instrumentation of Dask workflows for provenance tracking and performance analysis.

HPC↗
DOE OSTI2024

Computational design of non-porous pH-responsive antibody nanoparticles

Abstract Programming protein nanomaterials to respond to changes in environmental conditions is a current challenge for protein design and is important for targeted delivery of biologics. Here we describe the design of octahedral non-porous nanoparticles with a targeting antibody on the two-fold symmetry axis, a designed trimer programmed to disassemble below a tunable pH transition point on the three-fold axis, and a designed tetramer on the four-fold symmetry axis. Designed non-covalent interfaces guide cooperative nanoparticle assembly from independently purified components, and a cryo-EM density map closely matches the computational design model. The designed nanoparticles can package protein and nucleic acid payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between 5.9 and 6.7. The ability to incorporate almost any antibody into a non-porous pH-dependent nanoparticle opens up new routes to antibody-directed targeted delivery.

Biochemistry & Molecular Biology↗
DOE OSTI2023

Development of a Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) Tool

As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles. The main challenge is that light-duty tools do not estimate real-time vehicle mass, a factor that has a disproportionate impact on the energy consumption of large commercial vehicles. The Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) tool advances the state of the art in evaluating electrification potential and infrastructure requirements for fleets of commercial vehicles. In this work, the HEVII tool is demonstrated with non-uniformly sampled telematics data from an existing fleet to assess the suitability for electrification of each individual vehicle, determine optimal locations for charging infrastructure to support a fleet of EVs and analyze associated costs. Payload mass is predicted using sparse ground-truth data for all input drive cycles and an initial data analysis is conducted to assess the characteristics driving behaviors and energy consumption of the fleet using an adaptable vehicle model. Battery size requirements are determined by applying a novel charger placement algorithm to maximize routes that are viable for EVs and balance time delays with infrastructure development costs. This work details and demonstrates the different aspects of the HEVII tool, presenting preliminary results from an example use case.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Integration of the Kromek D3S Detector and Spot Robot For Secondary Inspections

Inspecting vehicles and containers for the presence of nuclear material is a challenging task for border control and security. When performed manually by inspectors, this task also has an associated risk of exposing the inspectors to unknown radiation. With the advent of agile, easy-to-program, quadruped robots like the Boston Dynamics Spot, automation of secondary inspection can improve the efficiency of the inspection process and alleviates the radiation risks to inspectors. In this project, Brookhaven National Laboratory and the University of Massachussetts at Lowell explored how to automate a simple secondary inspection mission. The Spot robot comes with its own software development kit (SDK) that allows clients/users to write custom code in the Python programming language to control the robot. Spot also has a payload computer called Spot-CORE, which runs the Ubuntu Linux operating system and allows users to integrate external sensors, such as a radiation detector, with Spot. In this study, the Kromek D3S detector has been integrated with Spot via the Spot-CORE, allowing Spot to capture gamma spectra and neutron counts for a specified acquisition period. Two custom routines, search and confirmation, have been developed and executed in this specified order. The search routine directs Spot to go around the nearest obstacle, e.g., vehicle and container, in a preset distance and step to collect gamma and neutron gross counts with the D3S detector. The radiation data and the robot location corresponding to each step are stored and fed to the confirmation routine at the end of the search. The confirmation routine then navigates Spot to the locations of the highest gamma or neutron counts to perform a long, e.g., one minute, measurement, and gives the operators the signature gamma spectra and neutron counts at the hotspots. This paper presents a detailed description of this automated system along with results of the preliminary tests in identifying the location and signature of a 137Cs radiation source in a vehicle.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

NACHOS, a CubeSat-based high-resolution UV-Visible hyperspectral imager for remote sensing of trace gases: system overview and science objectives

Here, the Nano-satellite Atmospheric Chemistry Hyperspectral Observation System (NACHOS) is a high-throughput (f/2.9), high spectral resolution (~1.3 nm optical resolution, 0.6 nm sampling) Offner-design hyperspectral imager operating in the 300-500 nm spectral region. The 1.5U instrument payload (1U optical system, 0.5U electronics module) is hosted by a 1.5U LANL-designed CubeSat bus to comprise a 3U complete satellite. Spectroscopically similar to NASA’s Ozone Monitoring Instrument (OMI), which provides wide-field global mapping of ozone and other gases at coarse spatial resolution, NACHOS fills the complementary niche of targeted measurements at much higher spatial resolution. With 350 across-track spatial pixels and a 15-degree across-track field of view, NACHOS will provide spectral imaging at roughly 0.4 km per pixel from 500 km altitude. NACHOS incorporates highly streamlined gas-retrieval algorithms for rapid onboard processing, alleviating the need to routinely downlink massive hyperspectral data cubes. We will discuss the instrument design, challenges in achieving mechanical robustness to launch vibration in such a compact instrument, the onboard calibration system, and gas-retrieval data downlink strategy. We will also discuss potential science missions, including monitoring of NO 2 as an easily detected proxy for anthropogenic fossil-fuel greenhouse gases, monitoring lowlevel SO 2 degassing at pre-eruptive volcanoes, H 2 CO from wildfires, and characterization of aerosols. The long-term vision is for a many-satellite constellation that could provide both high spatial resolution and frequent revisits for selected targets of interest. As an initial technology demonstration of this vision, the NACHOS project is currently slated to launch two CubeSats in early 2022.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

OPTIMUS{sup TM} Packaging for Intermediate Level Wastes and Spent Fuel - 20129

NAC's OPTIMUS{sup TM} packaging is a family of Type B(U)F transportation packages designed for maximum flexibility and cost-efficiency to support shipment of a wide range of challenging wastes and materials. They are small, modular packaging designs meeting DOT weight limits for road transport. OPTIMUS{sup TM} contents include low level waste, mixed low-level waste, irradiated fuel waste and intermediate level waste. Contents can also include aerosol cans with compressed gas and liquefied gas propellants and standard DOT 3E lecture bottles for shipment to treatment facilities. OPTIMUS{sup TM} packaging provides a cost-effective solution for challenging and unique waste contents combined with design simplicity and operational flexibility meeting the requirements of both SSR-6 and 10 CFR 71 for Type B(U)F packaging. The modular design of the packaging components combined with the flexibility to add modified internals for enhanced packaging performance makes OPTIMUS{sup TM} the preferred solution for many radioactive material transportation needs. The OPTIMUS{sup TM} product line currently includes two packaging designs; OPTIMUS{sup TM}-L and OPTIMUS{sup TM}-H. OPTIMUS{sup TM}-L is a lightweight transportation packaging intended for low-activity wastes, whereas OPTIMUS{sup TM}-H is a larger, heavier package intended for high-activities wastes. Due to its small size and weight, six (6) to ten (10) OPTIMUS{sup TM}-L packages can be accommodated on a single legal-weight truck shipment, depending on the weight of the contents. For typical payloads, two (2) OPTIMUS{sup TM}-H packages can be accommodated on a single legal-weight truck shipment. The OPTIMUS{sup TM} packaging share the same cask containment vessel (CCV) in the OPTIMUS{sup TM}-H and OPTIMUS{sup TM}-L. The large cavity size of the CCV, which can accommodate a 416-liter (110-gallon) drum, combined with the small size, low weight and modularity of the OPTIMUS{sup TM} packaging provides unmatched flexibility. In this paper, NAC provides a technical overview of the OPTIMUS{sup TM} packaging and identifies the design features and technology advancements making the OPTIMUS{sup TM} a readily adaptable and flexible solution for packaging processing facilities, reactor and decommissioning wastes. Optimized shielding performance through the addition of internal shielding components and alternative shipping configurations are discussed. In addition, an overview of the first major deployment of the OPTIMUS{sup TM} packaging for the Whiteshell Laboratories Closure Project (WLCP) is discussed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Emulation and Adversarial Analysis of EV Charging Networks

In the effort of decarbonization and evolution of the modern electrical grid, electric vehicles (EVs) play a key part to transform the grid. However, due to the rapid adoption of EVs and the demand of the charging infrastructure required to power said EVs, risk of a cyber-attack may impose serious consequences. There is a need to analyze and protect the charging ecosystem infrastructure from cyber threats before it reaches wide-scale deployment. In an effort to secure vehicle to grid (V2G) communications, standardization is necessary for continued reliable system operation. The protocol ISO 15118 outlines controls and practices that should be implemented for secure vehicle to grid (V2G) communications. The standard is gaining momentum for American markets as the demand for EV infrastructure grows. The adoption of ISO 15118 in American markets poses several challenges: the deployment of a public key infrastructure (PKI) as outlined within the standard, interoperability of charging different EVs with chargers from different manufactures using the PKI, and scaling the ecosystem to meet the demand while managing risks. This project was created to understand potential cyber and scaling challenges of PKI for EV infrastructure through utilizing a series of emulated components mapping to what exists in the EV ecosystem today, and the components of the PKI that are under development. The key nodes within the emulation that are under development are: electric vehicle (EV), electric vehicle supply equipment (EVSE), charge network operator (CNO), certificate authority (CA), and online certificate status protocol (OCSP) that must all interact using secure and trusted communications. With these emulated components and utilizing orchestration methods to rapidly deploy and scale the components, the ability to analyze risks of the ecosystem and address gaps before the PKI ecosystem is fully deployed to production should yield a more robust and mature production charging infrastructure. Our approach will use a modular architecture of virtual machines within an orchestration platform and will target scales of 100s, 1000s, and 10,000s of entities interacting. The core research questions trying to be answered with this scope of work are: what are the impacts of a rogue CA, what are the risks of certificate revocation list (CRL) management, what is the value of OCSP stapling, what components are vulnerable to DOS attacks, and what test effective payloads may impact the components.

charging ecosystem↗
DOE OSTI2024

Tools for genetic engineering and gene expression control in Novosphingobium aromaticivorans and Rhodobacter sphaeroides

ABSTRACT Alphaproteobacteria have a variety of cellular and metabolic features that provide important insights into biological systems and enable biotechnologies. For example, some species are capable of converting plant biomass into valuable biofuels and bioproducts that have the potential to contribute to the sustainable bioeconomy. Among the Alphaproteobacteria, Novosphingobium aromaticivorans , Rhodobacter sphaeroides , and Zymomonas mobilis show promise as organisms that can be engineered to convert extracted plant lignin or sugars into bioproducts and biofuels. Genetic manipulation of these bacteria is needed to introduce engineered pathways and modulate expression of native genes with the goal of enhancing bioproduct output. Although recent work has expanded the genetic toolkit for Z. mobilis , N. aromaticivorans and R. sphaeroides still need facile, reliable approaches to deliver genetic payloads to the genome and to control gene expression. Here, we expand the platform of genetic tools for N. aromaticivorans and R. sphaeroides to address these issues. We demonstrate that Tn 7 transposition is an effective approach for introducing engineered DNA into the chromosome of N. aromaticivorans and R. sphaeroides . We screen a synthetic promoter library to identify isopropyl β-D-1-thiogalactopyranoside-inducible promoters with regulated activity in both organisms (up to ~15-fold induction in N. aromaticivorans and ~5-fold induction in R. sphaeroides ). Combining Tn 7 integration with promoters from our library, we establish CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) interference systems for N. aromaticivorans and R. sphaeroides (up to ~10-fold knockdown in N. aromaticivorans and R. sphaeroides ) that can target essential genes and modulate engineered pathways. We anticipate that these systems will greatly facilitate both genetic engineering and gene function discovery efforts in these species and other Alphaproteobacteria. IMPORTANCE It is important to increase our understanding of the microbial world to improve health, agriculture, the environment, and biotechnology. For example, building a sustainable bioeconomy depends on the efficient conversion of plant material to valuable biofuels and bioproducts by microbes. One limitation in this conversion process is that microbes with otherwise promising properties for conversion are challenging to genetically engineer. Here we report genetic tools for Novosphingobium aromaticivorans and Rhodobacter sphaeroides that add to the burgeoning set of tools available for genome engineering and gene expression in Alphaproteobacteria. Our approaches allow straightforward insertion of engineered pathways into the N. aromaticivorans or R. sphaeroides genome and control of gene expression by inducing genes with synthetic promoters or repressing genes using CRISPR interference. These tools can be used in future work to gain additional insight into these and other Alphaproteobacteria and to aid in optimizing yield of biofuels and bioproducts.

Hall, Ashley N.↗