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At least 361 records · Page 20

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

New Developments in Retropropulsion Testing for Mars Entry, Descent and Landing

NASA’s plans for landing human-scale payloads on Mars in the next decade require that retrorockets be used to decelerate the atmospheric entry vehicle continuously from supersonic conditions through soft touchdown. Conventional Mars entry vehicle architectures that include a single parachute for supersonic-to-subsonic descent are not scalable to the sizes needed to land humans on Mars (~20 metric tons). The major aerosciences risks are the uncertainties in predicting aerodynamic stability and performance during powered free-flight and landing. These risks are influenced partially by current limitations in relevant data and testing methods. Consequently, trajectory simulations currently depend on unvalidated powered descent and landing aerodynamics models. NASA engineers have identified gaps in testing methods that, if addressed, would improve the ability to validate these models. There are gaps in capabilities to test multi-engine hot-gas retropropulsion systems in US wind tunnels. This is partially due to the successful use of parachutes as decelerators for human spaceflight at Earth and for the entire Mars lander program to date. Retropulsion test data historically and to this day are limited to using high pressure air jets, at comparatively low temperatures,as engine plume simulants on subscale wind tunnel models. Additionally, the ability to directly measure aerodynamic interference force and moments is limited by existing flow-through balance capabilities. This paper briefly covers historical and recent test data, and identifies new ground test techniques as a means to provide more relevant test data for powered flight and landing aerodynamic model validation.These techniques include using heated inert gases as a substitute for combustion products, additively manufactured 6-component flow-through force and moment balances, and off-body quantitative diagnostic measurements.

Retropropulsion↗

NASA NTRS2012

Next Generation Scalable Spaceborne GNSS Science Receiver

This paper will describe the TriG architecture, and how the new features will benefit the next-generation of global network instruments, as well as current test results.

Radio Occultation↗

DOE OSTI2022

Scalable Gas Diffusion Electrode Fabrication for Electrochemical CO 2 Reduction Using Physical Vapor Deposition Methods

Electrochemical CO 2 reduction (ECR) promises the replacement of fossil fuels as the source of feedstock chemicals and seasonal storage of renewable energy. While much progress has been made in catalyst development and electrochemical reactor design, few studies have addressed the effect of catalyst integration on device performance. Using a microfluidic gas diffusion electrolyzer, we systematically studied the effect of thickness and the morphology of electron beam (EB) and magnetron-sputtered (MS) Cu catalyst coatings on ECR performance. We observed that EB-Cu outperforms MS-Cu in current density, selectivity, and energy efficiency, with 400 nm thick catalyst coatings performing the best. Additionally, the superior performance of EB-Cu catalysts is assigned to their faceted surface morphology and sharper Cu/gas diffusion layer interface, which increases their hydrophobicity. Tests in a large-scale zero-gap electrolyzer yielded similar product selectivity distributions with an ethylene Faradaic efficiency of 39% at 200 mA/cm 2 , demonstrating the scalability for industrial ECR applications.

36 MATERIALS SCIENCE↗

NASA NTRS1999

ACTS 118x Final Report High-Speed TCP Interoperability Testing

With the recent explosion of the Internet and the enormous business opportunities available to communication system providers, great interest has developed in improving the efficiency of data transfer using the Transmission Control Protocol (TCP) of the Internet Protocol (IP) suite. The satellite system providers are interested in solving TCP efficiency problems associated with long delays and error-prone links. Similarly, the terrestrial community is interested in solving TCP problems over high-bandwidth links. Whereas the wireless community is interested in improving TCP performance over bandwidth constrained, error-prone links. NASA realized that solutions had already been proposed for most of the problems associated with efficient data transfer over large bandwidth-delay links (which include satellite links). The solutions are detailed in various Internet Engineering Task Force (IETF) Request for Comments (RFCs). Unfortunately, most of these solutions had not been tested at high-speed (155+ Mbps). Therefore, the NASA's ACTS experiments program initiated a series of TCP experiments to demonstrate scalability of TCP/IP and determine how far the protocol can be optimized over a 622 Mbps satellite link. These experiments were known as the 118i and 118j experiments. During the 118i and 118j experiments, NASA worked closely with SUN Microsystems and FORE Systems to improve the operating system, TCP stacks. and network interface cards and drivers. We were able to obtain instantaneous data throughput rates of greater than 520 Mbps and average throughput rates of 470 Mbps using TCP over Asynchronous Transfer Mode (ATM) over a 622 Mbps Synchronous Optical Network (SONET) OC12 link. Following the success of these experiments and the successful government/industry collaboration, a new series of experiments. the 118x experiments. were developed.

Ivancic, William D.↗

NASA NTRS2007

Performance of the NEXT Engineering Model Power Processing Unit

The NASA s Evolutionary Xenon Thruster (NEXT) project is developing an advanced ion propulsion system for future NASA missions for solar system exploration. An engineering model (EM) power processing unit (PPU) for the NEXT project was designed and fabricated by L-3 Communications under contract with NASA Glenn Research Center (GRC). This modular PPU is capable of processing up from 0.5 to 7.0 kW of output power for the NEXT ion thruster. Its design includes many significant improvements for better performance over the state-of-the-art PPU. The most significant difference is the beam supply which is comprised of six modules and capable of very efficient operation through a wide voltage range because of innovative features like dual controls, module addressing, and a high current mode. The low voltage power supplies are based on elements of the previously validated NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) PPU. The highly modular construction of the PPU resulted in improved manufacturability, simpler scalability, and lower cost. This paper describes the design of the EM PPU and the results of the bench-top performance tests.

Pinero, Luis R.↗

NASA NTRS2012

TriG: Next Generation Scalable Spaceborne GNSS Receiver

TriG is the next generation NASA scalable space GNSS Science Receiver. It will track all GNSS and additional signals (i.e. GPS, GLONASS, Galileo, Compass and Doris). Scalable 3U architecture and fully software and firmware recofigurable, enabling optimization to meet specific mission requirements. TriG GNSS EM is currently undergoing testing and is expected to complete full performance testing later this year.

Global Navigation Satellite Systems (GNSS)↗

DOE OSTI2020

Advanced control sequences and FDD technology. Just shiny objects, or ready for scale?

Innovations in commercial building control sequences (ASHRAE guideline 36) and fault detection and diagnostics (FDD) technology have the potential to transform existing building operational efficiency by realizing whole-building level savings on the order of 15% and higher. However, several technical and market barriers related to up-front estimation of achievable savings, verifying implementation, and ensuring persistence are slowing down their adoption as a core offering through diverse owner-funded initiatives and rate-payer funded programs. This paper describes a suite of solutions to overcome these barriers to program delivery of advanced HVAC controls integrated with FDD energy management and information system (EMIS) technology. First, the Guideline 36 conformance test offers an automated method to confirm correct sequence implementation by the manufacturer, before field deployment. A successful test of a controller was conducted using a new manufacturer-independent hardware-in-the-loop testbed demonstrating the viability and scalability of this approach. Second, the Guideline 36 energy savings calculator uses modeling paired with high-level user inputs to estimate building-specific savings potential, target cost effective implementation and minimize uncertainty. Initial results indicate the baseline control sequences significantly impact energy savings, however, as much as 50% savings may be possible for the worst-case baseline scenario. Third, a functional specification provides minimum recommended EMIS-FDD capabilities, and best practices to integrate the technology into organizational practice and ensure that advanced control sequences provide persistent savings.

Pritoni, Marco↗

DOE OSTI2020

Reducing communication in algebraic multigrid with multi-step node aware communication

Algebraic multigrid (AMG) is often viewed as a scalable [Formula: see text] solver for sparse linear systems. Yet, AMG lacks parallel scalability due to increasingly large costs associated with communication, both in the initial construction of a multigrid hierarchy and in the iterative solve phase. This work introduces a parallel implementation of AMG that reduces the cost of communication, yielding improved parallel scalability. It is common in Message Passing Interface (MPI), particularly in the MPI-everywhere approach, to arrange inter-process communication, so that communication is transported regardless of the location of the send and receive processes. Performance tests show notable differences in the cost of intra- and internode communication, motivating a restructuring of communication. In this case, the communication schedule takes advantage of the less costly intra-node communication, reducing both the number and the size of internode messages. Node-centric communication extends to the range of components in both the setup and solve phase of AMG, yielding an increase in the weak and strong scaling of the entire method.

Computer Science↗

DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

DOE OSTI2016

Chevron Natural Gas Carbon Capture Technology Testing Project (Final Technical Report)

The objective of this project was to design, construct, commission, and operate an engineering scale post combustion carbon capture system to validate the technical maturity, operability, and scalability of Svante’s VeloxoTherm™ solid sorbent carbon capture technology under representative flue gas conditions. The project was executed at Chevron’s Kern River oil field in the San Joaquin Valley of California and evaluated carbon capture performance using slipstream flue gas from natural gas fired once through steam generators (OTSG), including indicative coal and natural gas combined cycle (NGCC) operating scenarios.

03 NATURAL GAS↗

DOE OSTI2025

A Review of Quantum Computing Technologies in Power System Optimization

As modern power grids increasingly integrate variable renewable generation, distributed energy resources, and energy storage systems, classical optimization techniques are facing unprecedented challenges. This review examines the emerging application of quantum computing to overcome these challenges in power system optimization, including optimal power flow (OPF), unit commitment (UC), economic dispatch (ED), and intelligent switching and topology optimization (IS-TO). Recent research has introduced various quantum methodologies—such as gate-based, annealing-based, variational algorithms, and quantum-inspired algorithms—to address the combinatorial complexity inherent in grid reconfiguration and energy management. The review summaries the quantum algorithms, quantum devices and the power system test cases, highlighting hybrid quantum–classical strategies that leverage the complementary strengths of both paradigms. Some quantum advantages have been observed, including theoretical speedup, accurate simulation results, scalable qubit usage, efficient QUBO mapping. In particular, the review emphasizes the importance of integrating quantum optimization techniques with classical control frameworks, these hybrid approaches demonstrate the potential to improve real-time grid management and operational reliability. A significant portion of the analysis is devoted to the practical limitations of current quantum devices. Present-day quantum hardware, operating in the noisy intermediate-scale quantum (NISQ) era, remains highly sensitive to noise and limited in qubit connectivity, which constrains the scale and accuracy of implemented algorithms. The review delves into specific challenges such as the need for qubit-efficient encoding techniques and error mitigation strategies that are critical for handling real-world grid optimization problems. In addition, the work draws attention to the performance discrepancies between theoretical quantum speedups and experimental validations, underscoring the importance of rigorous benchmark studies using representative power grid test cases. In summary, this review highlights both the promise and limitations of quantum computing for power system optimization. It provides a comprehensive overview of the state-of-the-art technologies, categorizes recent advancements in algorithm design, and discusses practical considerations for implementation, and serves as an informative resource on current research. Future research directions include developing robust hybrid frameworks, advancing qubit-efficient formulations, and scaling up experimental demonstrations to confirm the theoretical advantages of quantum methods in large-scale power system operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

GR-Athena++: Puncture Evolutions on Vertex-centered Oct-tree Adaptive Mesh Refinement

Numerical relativity is central to the investigation of astrophysical sources in the dynamical and strong-field gravity regime, such as binary black hole and neutron star coalescences. Current challenges set by gravitational-wave and multimessenger astronomy call for highly performant and scalable codes on modern massively parallel architectures. We present GR-Athena++, a general-relativistic, high-order, vertex-centered solver that extends the oct-tree, adaptive mesh refinement capabilities of the astrophysical (radiation) magnetohydrodynamics code Athena++. To simulate dynamical spacetimes, GR-Athena++ uses the Z4c evolution scheme of numerical relativity coupled to the moving puncture gauge. We demonstrate stable and accurate binary black hole merger evolutions via extensive convergence testing, cross-code validation, and verification against state-of-the-art effective-one-body waveforms. GR-Athena++ leverages the task-based parallelism paradigm of Athena++ to achieve excellent scalability. We measure strong-scaling efficiencies above 95% for up to ~1.2 × 10 4 CPUs and excellent weak scaling is shown up to ~10 5 CPUs in a production binary black hole setup with adaptive mesh refinement. GR-Athena++ thus allows for the robust simulation of compact binary coalescences and offers a viable path toward numerical relativity at exascale.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Engineering modular enzyme assembly: synthetic interface strategies for natural products biosynthesis applications

Covering: 2020 to 2025Natural products remain indispensable sources of therapeutic and bioactive compounds, yet traditional discovery strategies are constrained by compound rediscovery. Modular biosynthetic enzymes, such as type I polyketide synthases (PKSs) and type A non-ribosomal peptide synthetases (NRPSs), offer promising platforms for combinatorial biosynthesis owing to their programmable architectures. However, practical implementation is frequently limited by inter-modular incompatibility and domain-specific interactions. This review highlights recent advances in modular enzyme assembly enabled by synthetic interfaces-including cognate docking domains, synthetic coiled-coils, SpyTag/SpyCatcher, and split inteins-which function as orthogonal, standardized connectors to facilitate post-translational complex formation. These interfaces support rational investigations into substrate specificity, module compatibility, and pathway derivatization as well as general enzyme clustering applications beyond PKS and NRPS systems. Synthetic interfaces can be integrated with computational tools to support a more systematic and scalable framework for modular enzyme engineering by providing predictive insights into domain compatibility and interface design. These approaches within iterative design-build-test-learn workflows can accelerate the programmable assembly of biosynthetic systems and expand the accessible chemical space for natural products.

Kim, Gahyeon↗

DOE OSTI2024

Enhancing Lattice Kinetic Schemes for Fluid Dynamics with Lattice-Equivariant Neural Networks

A new class of equivariant neural networks is presented, hereby dubbed lattice-equivariant neural networks (LENNs), designed to satisfy local symmetries of a lattice structure. The approach develops within a recently introduced framework aimed at learning neural network-based surrogate models’ lattice Boltzmann collision operators. Whenever neural networks are employed to model physical systems, respecting symmetries and equivariance properties has been shown to be key for accuracy, numerical stability, and performance. Here, hinging on ideas from group representation theory, trainable layers are defined whose algebraic structure is equivariant with respect to the symmetries of the lattice cell. In this work, the presented method naturally allows for efficient implementations, in terms of both memory usage and computational costs, supporting scalable training/testing for lattices in two spatial dimensions and higher (in which the size of symmetry group grows). The approach is validated and tested considering 2D and 3D flowing dynamics, both in laminar and turbulent regimes. It is compared with group-averaged-based symmetric networks and with plain, nonsymmetric, networks, showing how the presented approach unlocks the (a posteriori) accuracy and training stability of the former models and the train/inference speed of the latter networks. (LENNs are about one order of magnitude faster than group-averaged networks in 3D.) The work in this paper opens toward practical use of machine learning-augmented lattice Boltzmann CFD in real-world simulations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Neuroevolution Application to Collaborative and Heuristics-Based Connected and Autonomous Vehicle Cohort Simulation at Uncontrolled Intersection

Artificial intelligence is gaining tremendous attractiveness and showing great success in solving various problems, such as simplifying optimal control derivation. This work focuses on the application of Neuroevolution to the control of Connected and Autonomous Vehicle (CAV) cohorts operating at uncontrolled intersections. The proposed method implementation’s simplicity, thanks to the inclusion of heuristics and effective real-time performance are demonstrated. The resulting architecture achieves nearly ideal operating conditions in keeping the average speeds close to the speed limit. It achieves twice as high mean speed throughput as a controlled intersection, hence enabling lower travel time and mitigating energy inefficiencies from stop-and-go vehicle dynamics. Low deviation from the road speed limit is hence continuously sustained for cohorts of at most 50 m long. This limitation can be mitigated with additional lanes that the cohorts can split into. The concept also allows the testing and implementation of fast-turning lanes by simply replicating and reconnecting the control architecture at each new road crossing, enabling high scalability for complex road network analysis. The controller is also successfully validated within a high-fidelity vehicle dynamic environment, showing its potential for driverless vehicle control in addition to offering a new traffic control simulation model for future autonomous operation studies.

Jacquelin, Frederic (ORCID:0000000183154344)↗

DOE OSTI2026

Integrated Transmission-Distribution Multi-Period Switching for Wildfire Risk Mitigation: Improving Speed and Scalability with Distributed Optimization: Preprint

With increasingly severe wildfire conditions driven by climate change, utilities must manage the risk of wildfire ignitions from electric power lines. During "public safety power shutoff'" events, utilities de-energize power lines to reduce wildfire ignition risk, which may result in load shedding. Distributed energy resources provide flexibility that can help support the system to reduce load shedding when lines are de-energized. We investigate a coordinated transmission-distribution optimization problem that balances wildfire risk mitigation and load shedding. We model distribution systems that include battery energy storage systems which may support loads when transmission lines are de-energized. This multi-period integrated transmission-distribution optimal switching problem jointly optimizes line switching decisions, the generators' setpoints, load shedding, and the batteries' states of charge, resulting in significant computational challenges. To improve scalability, we decompose the problem over both space and time and apply a distributed optimization algorithm. Using a large-scale synthetic California test case with realistic distribution models and real wildfire risk data, we show that distributed optimization can solve large-scale multi-period switching problems that are otherwise intractable for centralized solvers. We also discuss challenges and future directions for improving the distributed algorithm's convergence performance as the number of time periods increases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Atomic Layer Deposition for Improved Biomass Conversion Catalysts

Heterogeneous catalysts are a key enabler of the transition towards a sustainable, bio-based economy for fuels and chemicals. However, the harsh conditions in many biomass conversion processes lead to nanoparticle sintering, support collapse, and metal leaching in conventional PGM catalysts. Next-generation catalysts must be developed to address these stability challenges. This presentation will discuss ongoing work between the Catalytic Carbon Transformation and Scale-Up Center at NREL and various industrial partners to develop scalable and cost-effective atomic layer deposition (ALD) coatings for improving the performance of biomass conversion catalysts. The substantial focus will be devoted to the benefits of TiO2 ALD coatings on supported Pd hydrogenation catalysts. Ten cycles of TiO2 ALD were found to dramatically improve the activity of a conventional Pd/Al2O3 catalyst towards aromatic hydrogenation, despite partial coverage of the Pd sites by the ALD layer. Subsequent advanced characterization and atomic-scale computational modeling revealed that the ALD coating weakened the adsorption strength of hydrogenation surface intermediates, leading to higher reaction rates. Reaction testing after exposure to sulfur impurities, high temperature oxidation, and hydrothermal treatment demonstrated the improved stability of the ALD-coated catalyst. Additionally, the ALD synthesis process was found to be scalable over two orders of magnitude with minimal deviation in synthesized catalyst properties. These results were contextualized with cost models of industrial ALD coating and aromatic hydrogenation processes to further refine the value proposition of ALD coatings. Given the demonstrated improvements in hydrogenation, TiO2 ALD coatings have also been applied to supported Pt catalysts for use in other biomass conversion reactions, such as hydrodeoxygenation for the production of sustainable aviation fuel (SAF) and the oxidation of glucose to bio-derived gluconic acid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Atomic Layer Deposition for Improved Biomass Conversion Catalysts

atomic layer deposition↗