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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Operation of Dual-T-Type Modular Multilevel Converter for Uninterrupted Power Supply Under Bridge Failures

Dual-T-type modular multilevel converter (DTMMC) is an alternative to the existing uninterrupted power supply (UPS) due to its advantage in flexible leg reusing, multiple power ports, and high operating efficiency. Here, in this article, a DTMMC-UPS, which has series configurations on both input/output ac sides, obtains high-voltage grid/load accessing interfaces is presented. In the described system, the fact that copies of T-type legs are employed makes semiconductor failure common to happen. Moreover, both the coupling between rectifier and inverter conversions and the confliction between intercell and inner-cell voltage balancing make fault-tolerant control a tough issue. In this article, the switch fault types are first clarified and diagnosed by the different impacts on normal operation. An improved voltage vector modulation is then deduced to facilitate the planning of proper primary switching patterns, to achieve rectifier side normal operation. The secondary alternated level-shifted pulsed-width modulation (LS-PWM) is also modified to achieve inverter side normal operation. The experiment results are supplied to verify the validity of the modulation-coordinated fault toleration strategy.

42 ENGINEERING↗
DOE OSTI2021

A Modular and Transferable Reinforcement Learning Framework for the Fleet Rebalancing Problem

Mobility on demand (MoD) systems show great promise in realizing flexible and efficient urban transportation. However, significant technical challenges arise from operational decision making associated with MoD vehicle dispatch and fleet rebalancing. For this reason, operators tend to employ simplified algorithms that have been demonstrated to work well in a particular setting. To help bridge the gap between novel and existing methods, we propose a modular framework for fleet rebalancing based on model-free reinforcement learning (RL) that can leverage an existing dispatch method to minimize system cost. In particular, by treating dispatch as part of the environment dynamics, a centralized agent can learn to intermittently direct the dispatcher to reposition free vehicles and mitigate against fleet imbalance. We formulate RL state and action spaces as distributions over a grid partitioning of the operating area, making the framework scalable and avoiding the complexities associated with multiagent RL. Numerical experiments, using real-world trip and network data, demonstrate that RL reduces waiting time by 28% to 38% for the same-day evaluation, 17% to 44% for cross-day evaluation, and 22% to 25% for cross-season evaluation compared with no rebalancing scenarios. This approach has several distinct advantages over baseline methods including: improved system cost; high degree of adaptability to the selected dispatch method; and the ability to perform scale-invariant transfer learning between problem instances with similar vehicle and request distributions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

A Novel Modular, Reconfigurable Battery Energy Storage System: Design, Control, and Experimentation

This paper presents a novel modular, reconfigurable battery energy storage system. The proposed design is characterized by a tight integration of reconfigurable power switches and DC/DC converters. This characteristic enables isolation of faulty cells from the system and allows fine power control for individual cells toward optimal system-level performance. An optimal power management approach is developed to extensively exploit the merits of the proposed design. Based on receding-horizon convex optimization, this approach aims to minimize the total power losses in charging/discharging while allocating the power in line with each cell’s condition to achieve state of-charge (SoC) and temperature balancing. By appropriate design, the approach manages to regulate the power of a cell across its full SoC range and guarantee the feasibility of the optimization problem. Here, we perform extensive simulations and further develop a lab-scale prototype to validate the proposed system design and power management approach.

25 ENERGY STORAGE↗
DOE OSTI2021

CAN-D: A Modular Four-Step Pipeline for Comprehensively Decoding Controller Area Network Data

Controller area networks (CANs) are a broadcast protocol for real-time communication of critical vehicle subsystems. Original equipment manufacturers of passenger vehicles hold secret their mappings of CAN data to vehicle signals, and these definitions vary according to make, model, and year. Without these mappings, the wealth of real-time vehicle information hidden in the CAN packets is uninterpretable, severely impeding vehicle-related research, including CAN cybersecurity and privacy studies, aftermarket tuning, efficiency and performance monitoring, and fault diagnosis to name a few. Guided by the four-part CAN signal definition, we present CAN-D (CAN-Decoder), a modular, four-step pipeline for identifying each signal's boundaries (start bit and length), endianness (byte ordering), signedness (bit-to-integer encoding), and by leveraging diagnostic standards, augmenting a subset of the extracted signals with meaningful, physical interpretation. En route to CAN-D, we provide a comprehensive review of the CAN signal reverse engineering research. All previous methods ignore endianness and signedness, rendering them incapable of decoding many standard CAN signal definitions. Incorporating endianness grows the search space from 128 to 4.72E21 signal tokenizations and introduces a web of changing dependencies. In response, we formulate, formally analyze, and provide an efficient solution to an optimization problem, allowing identification of the optimal set of signal boundaries and byte orderings. In addition, we provide two novel, state-of-the-art signal boundary classifiers—both of which are superior to previous approaches in precision and recall in three different test scenarios—and the first signedness classification algorithm, which exhibits a $>$ 97% F-score. Altogether, CAN-D is the only solution with the potential to extract any CAN signal that is also the state of the art. In evaluation on 10 vehicles of different makes, CAN-D's average $\ell ^1$ error is five times better (81% less) than all previous methods and exhibits lower average error, even when considering only signals that meet prior methods’ assumptions. Finally, CAN-D is implemented in lightweight hardware, allowing for an on-board diagnostic (OBD-II) plugin for real-time in-vehicle CAN decoding.

42 ENGINEERING↗
DOE OSTI2021

A Modular Mechanism for Downhole Weight-on-Bit and Torque Reaction in Small Diameter Boreholes

Drilling systems that use downhole rotation must react torque either through the drill-string or near the motor to achieve effective drilling performance. Problems with drill-string loading such as buckling, friction, and twist become more severe as hole diameter decreases. Therefore, for small holes, reacting torque downhole without interfering with the application of weight-on-bit, is preferred. In this paper, we present a novel mechanism that enables effective and controllable downhole weight on bit transmission and torque reaction. This scalable design achieves its unique performance through four key features: (1) mechanical advantage based on geometry, (2) direction dependent behavior using rolling and sliding contact, (3) modular scalability by combining modules in series, and (4) torque reaction and weight on bit that are proportional to applied axial force. As a result, simple mechanical devices can be used to react large torques while allowing controlled force to be transmitted to the drill bit. We outline our design, provide theoretical predictions of performance, and validate the results using full-scale testing. The experimental results include laboratory studies as well as limited field testing using a percussive hammer. These results demonstrate effective torque reaction, axial force transmission, favorable scaling with multiple modules, and predictable performance that is proportional to applied force.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

BI-LEVEL OPTIMIZATION FOR ELECTRICITY TRANSACTION IN SMART COMMUNITY WITH MODULAR PUMP HYDRO STORAGE

Grid integration of the increasing distributed energy resources could be challenging in terms of new infrastructure investment, power grid stability, etc. To resolve more renewables locally and reduce the need for extensive electricity transmission, a community energy transaction market is assumed with market operator as the leader whose responsibility is to generate local energy prices and clear the energy transaction payment among the prosumers (followers). The leader and multi-followers have competitive objectives of revenue maximization and operational cost minimization. This non-cooperative leader-follower (Stackelberg) game is formulated using a bi-level optimization framework, where a novel modular pump hydro storage technology (GLIDES system) is set as an upper level market operator, and the lower level prosumers are nearby commercial buildings. The best responses of the lower level model could be derived by necessary optimality conditions, and thus the bi-level model could be transformed into single level optimization model via replacing the lower level model by its Karush-Kuhn-Tucker (KKT) necessary conditions. Several experiments have been designed to compare the local energy transaction behavior and profit distribution with the different demand response levels and different local price structures. The experimental results indicate that the lower level prosumers could benefit the most when local buying and selling prices are equal, while maximum revenue potential for the upper level agent could be reached with non-equal trading prices.

Chen, Yang↗
DOE OSTI2021

Modular polyketide synthase contains two reaction chambers that operate asynchronously

Type I modular polyketide synthases are homodimeric multidomain assembly line enzymes that synthesize a variety of polyketide natural products by performing polyketide chain extension and β-keto group modification reactions. We determined the 2.4-angstrom-resolution x-ray crystal structure and the 3.1-angstrom-resolution cryo–electron microscopy structure of the Lsd14 polyketide synthase, stalled at the transacylation and condensation steps, respectively. These structures revealed how the constituent domains are positioned relative to each other, how they rearrange depending on the step in the reaction cycle, and the specific interactions formed between the domains. Like the evolutionarily related mammalian fatty acid synthase, Lsd14 contains two reaction chambers, but only one chamber in Lsd14 has the full complement of catalytic domains, indicating that only one chamber produces the polyketide product at any given time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

MVP: a modular viromics pipeline to identify, filter, cluster, annotate, and bin viruses from metagenomes

While numerous computational frameworks and workflows are available for recovering prokaryote and eukaryote genomes from metagenome data, only a limited number of pipelines are designed specifically for viromics analysis. With many viromics tools developed in the last few years alone, it can be challenging for scientists with limited bioinformatics experience to easily recover, evaluate quality, annotate genes, dereplicate, assign taxonomy, and calculate relative abundance and coverage of viral genomes using state-of-the-art methods and standards. Here, we describe Modular Viromics Pipeline (MVP) v.1.0, a user-friendly pipeline written in Python and providing a simple framework to perform standard viromics analyses. MVP combines multiple tools to enable viral genome identification, characterization of genome quality, filtering, clustering, taxonomic and functional annotation, genome binning, and comprehensive summaries of results that can be used for downstream ecological analyses. Overall, MVP provides a standardized and reproducible pipeline for both extensive and robust characterization of viruses from large-scale sequencing data including metagenomes, metatranscriptomes, viromes, and isolate genomes. As a typical use case, we show how the entire MVP pipeline can be applied to a set of 20 metagenomes from wetland sediments using only 10 modules executed via command lines, leading to the identification of 11,656 viral contigs and 8,145 viral operational taxonomic units (vOTUs) displaying a clear beta-diversity pattern. Further, acting as a dynamic wrapper, MVP is designed to continuously incorporate updates and integrate new tools, ensuring its ongoing relevance in the rapidly evolving field of viromics. MVP is available at https://gitlab.com/ccoclet/mvp and as versioned packages in PyPi and Conda.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

SODA Synthesizer: an Open-source, Multi-level, Modular, Extensible Compiler from High-level Frameworks to Silicon

The SODA Synthesizer is an open-source modular, end-to-end hardware compiler framework. The SODA frontend, developed in MLIR, performs system-level design, code partitioning, and high-level optimizations to prepare the specifications for the hardware synthesis. The backend is based on a state-of-the-art high-level synthesis tool, and generates the final hardware design. The backend can interface with logic synthesis tools for field programmable gate arrays or with commercial and open-source logic synthesis tools for application-specific integrated circuits. We discuss the opportunities and challenges in integrating with commercial and open-source tools both at the frontend and backend, and the unique opportunities that an open-source hardware design ecosystem provides.

Bohm Agostini, Nicolas↗
DOE OSTI2025

OmniFed: A Modular Framework for Configurable Federated Learning from Edge to HPC

Federated Learning (FL) is critical for edge and High Performance Computing (HPC) where data is not centralized and privacy is crucial. We present OmniFed, a modular framework designed around decoupling and clear separation of concerns for configuration, orchestration, communication, and training logic. Its architecture supports configuration-driven prototyping and code-level override-what-you-need customization. We also support different topologies, mixed communication protocols within a single deployment, and popular training algorithms. It also offers optional privacy mechanisms including Differential Privacy (DP), Homomorphic Encryption (HE), and Secure Aggregation (SA), as well as compression strategies. These capabilities are exposed through well-defined extension points, allowing users to customize topology and orchestration, learning logic, and privacy/compression plugins, all while preserving the integrity of the core system. We evaluate multiple models and algorithms to measure various performance metrics. By unifying topology configuration, mixed-protocol communication, and pluggable modules in one stack, OmniFed streamlines FL deployment across heterogeneous environments. Github repository is available at https://github.com/at-aaims/OmniFed.

Tyagi, Sahil [ORNL] (ORCID:0009000783144745)↗
DOE OSTI2024

MODAQ (Modular Offshore Data Acquisition System) [SWR-24-58]

The National Renewable Energy Laboratory (NREL) has developed a data acquisition system to support laboratory (component) and in-water validation and testing of Marine Renewable Energy (MRE) technologies. The Modular Ocean Data AcQuisition System (MODAQ) is a robust system built on industrial grade hardware that can acquire high-quality and summary data from many sensor and instrument types. MODAQ includes modules to perform real-time QC screening, system health monitoring, and send alerts. MODAQ is also part of a larger data management, processing, visualization, and archiving system.

Raye, Robert↗
DOE OSTI2024

MODAQ 2.0 (Modular Ocean Data AcQuisition System v2.0) [SWR-24-138]

MODAQ 2.0 is the continuation of the Modular Ocean/Offshore Data AcQuisition system which offers new benefits of being based on generally available hardware and open-source development tools. The MODAQ 2.0 project is the amalgamation of ROS packages, tools, and guidance for developing data acquisition and control applications for marine energy devices using a ROS2 based architecture. The MODAQ 2.0 Reference Design includes several packages that are targeted for the marine energy sector and allow most developers with a basic background in programming to spin up a high-quality DAQ and control system. It is comprised of multiple software repositories which can be found at the MODAQ2 GitHub Organization: https://github.com/NREL-MODAQ2

Nichols, Casey↗
DOE OSTI2024

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗
DOE OSTI2022

Modular Adaptive Packing for Integrally Cooled Absorbers

Process intensification is one cornerstone in ION Clean Energy’s (ION) efforts to lowering CO2 capture cost. ION has modeled, designed, and fabricated an innovative gas-liquid contactor known as Modular Adaptive Packing (MAP). During two successful SBIR Phase I and II projects entitled: “Rapid Design and Testing of Novel Gas-Liquid Contacting Devices for Post-Combustion CO2 Capture via 3D-printing”, ION developed and proved this new technology at bench scale. MAP, a 3D-printed lattice-structured packing, combines the absorber gas/liquid contactor with an innovative in-situ heat-exchanger. Thanks to the capabilities of 3D-printing, the lattice structure of MAP contains hollow channels through which coolant water can be pumped to remove the heat of reaction from CO2 absorption. ION refers to this novel method of heat exchange as intracooling. After 25.4 cm (10 in) diameter MAP modules were fabricated, ION built and tested a packing characterization rig at its pilot facility in Boulder, Colorado, U.S.A. To provide baseline results for the characterization rig, ION tested Sulzer’s Mellapak™ 250Y (MP250Y) as a standard structured packing. ION’s MAP was then compared directly to the baseline MP250Y packing to evaluate key indicators including pressure drop, liquid hold-up, and effective area. MAP has a higher pressure drop than MP250Y at the same gas velocities in addition to greater liquid holdup. However, ION found that MAP displays a higher wetting coverage of 93% compared to 65% for MP250Y and reduces shearing forces that result in undesirable droplet formation. Using Optimized Gas Treating’s (OGT) rate-based simulation software ProTreat®, a conceptual evaluation of MAP was modeled for a CO2 absorber using 30 wt% MEA solvent over a range of lean loadings at 90% CO2 capture from a coal-fired power plant. ION modeled a 25-meter column absorber for both the standard MP250Y packing and a hybrid column. The hybrid absorber contained 10 m of MP250Y packing at the top and bottom with the middle 5 meters comprised of MAP. Compared to a traditional intercooled absorber, MAP can remove 22% more heat and increase overall MEA carrying capacity by 4% without increasing overall pressure drop.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Beurling-Selberg extremization and modular bootstrap at high energies

We consider previously derived upper and lower bounds on the number of operators in a window of scaling dimensions [\Delta - \delta,\Delta + \delta] [ Δ − δ , Δ + δ ] at asymptotically large \Delta Δ in 2d unitary modular invariant CFTs. These bounds depend on a choice of functions that majorize and minorize the characteristic function of the interval [\Delta - \delta,\Delta + \delta] [ Δ − δ , Δ + δ ] and have Fourier transforms of finite support. The optimization of the bounds over this choice turns out to be exactly the Beurling-Selberg extremization problem, widely known in analytic number theory. We review solutions of this problem and present the corresponding bounds on the number of operators for any \delta \geq 0 δ ≥ 0 . When 2\delta \in \mathbb Z_{\geq 0} 2 δ ∈ ℤ ≥ 0 the bounds are saturated by known partition functions with integer-spaced spectra. Similar results apply to operators of fixed spin and Virasoro primaries in c>1 c > 1 theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Low cost modular plasma system for reforming of natural gas

The initial aim of this project was to develop a low-cost compact, modularly scalable, point of use, on demand production system for the reforming of natural gas (NG) into products such as acetylene, hydrogen and other related hydrocarbons. Based on a pulsed dielectric barrier discharge (DBD), the fast rising voltage pulses produced by the system causes the dielectric breakdown of the gas to lag behind the rapid voltage increase so that a voltage greater than the static breakdown voltage of the gas, called an overvoltage, is briefly attained. The century long commercial use of the DBD discharge to push the highly endothermic oxygen to ozone reaction served as an additional motivation. The project meets the recommendations of the National Research Council 2007 report on plasma science for a greater investment in low temperature plasma science and engineering. An important finding is that the method investigated has a high specific energy requirement (SER) of the order of 1,000 to 5,000 kWh per kg of hydrogen, and a corresponding low efficiency of only ~0.1 to 0.5% of converting electrical into chemical (ΔH, ΔG) energy. This compares unfavorably with 52 kWh/kgH 2 required for NG thermal plasma reforming, or a pulsed spark discharge, Lotfalipour et. al, and Gao et. al. (For comparison electrolysis of water into hydrogen and oxygen gas requires only 45 to 80kWh/kgH 2 ). This project garnered data with different reactor configurations, materials, gases and mixtures including NG, methane, hydrogen, propane, argon, nitrogen and air, gap sizes ranging from 0.5 to 4.1 mm, electrode areas from 5 to 460 cm, voltages to 27 kV, pulse frequencies to 20 kHz and peak currents into the hundreds of amperes, temperatures to 625 °C and pressures from 15 mbar to 2 bar. An SRS 300 residual gas analyzer (RGA) yielded quadrupole mass spectrometry (QMS) data on the reformate. To analyze the data we extended the public domain software OpenChrom®, Wenig, to QMS data, yielding accurate identification and quantitative data on reformate products. This extension of OpenChrom® is applicable beyond this project and is a significant contribution to the general community of researchers. The documentation is available on the internet, see Whitlock, and a copy has been appended to this report. The main product of methane and natural gas plasma reforming is hydrogen, constituting ~90% of the products, followed by 1% to 10% ethane, propane, ethylene, acetylene and isobutene. Neopentane, propene, butane and pentane constitute less than 1 % of product. Adding a nickel catalyst increases the selectivity for hydrogen. Carbon nanosheets (graphene), a product of commercial interest, were synthesized by plasma reforming of acetylene at low pressure. The reformate analysis shows hat saturated and branched hydrocarbons are favored compared with unsaturated and linear hydrocarbons. For example, ethane, propane, iso-butane, 2-methyl butane, and 2-methyl pentane are produced in higher amounts compared with unsaturated and linear components. At low pressure acetylene and ethylene production rate is higher and propane production lower. We developed a recirculating system in which hydrogen is removed through a permeable membrane as fast as it is being produced by the reactor and the remaining products are recirculated at a high flow rate of several liters per minute. This keeps the concentration of H 2 in the reactor low, while achieving a total output concentration of 79%, high enough for pressure swing adsorption to be used for further purification. The recirculating system could be used with other gas reforming technologies. We report on four different reactors,1) a spark discharge reactor, 2) a standard DBD cylindrical reactor, 3) a small DBD reactor where catalyst powder can be quickly loaded onto a carrier to investigate the effect of the plasma on the catalyst and the effectiveness of the of the catalyst in promoting gas reformation and 4) a configurable DBD reactor to study the performance effects of dielectric selection, electrode gap distance, and electrode/dielectric interface on plasma reactor operation. This project achieved a commercializable 1kW plasma system including reactors a plasma pulse generator and a gas supply module.

03 NATURAL GAS↗
DOE OSTI2019

Integrated Electric Drive with HV 2 Modular Electric Machine and SiC Based Power Converters (Final Report)

An innovative high performance, high speed electric drive is designed, fabricated and tested. The drive is based on the modular multilevel converter (MMC) topology and is synthesized using power electronic building blocks (submodules) that utilize the newest generation of silicon-carbide (SiC) semiconductors. Power modules from two suppliers are investigated, characterized and the one showing better performance selected. A prototype MMC submodule is designed, built and tested in the lab. Simultaneously, control hardware and software are implemented and tested using real-time simulators. After verification of each of the subsystems, all subsystems are integrated to form a DC/AC converter-based drive. Multiple configurations are assembled and tested, and operation in variable voltages and frequencies, up to 4,160 V (line-to-line, rms), 140 A (rms) and 0-1,000 Hz is achieved. The efficiency of the drive system accomplished in the project is higher than 99.2% and the volume is 70% smaller than that of state-of-the art drives made using conventional technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

O 2 Binding Materials and highly Efficient Modular System for Oxygen Production

The overall objective of this project was to develop innovative oxygen separation materials and technologies based on using oxygen carriers in solid form to reversibly bind oxygen for efficient separation of air to produce greater than 95% purity of oxygen (O 2 ). These materials were then be made into solid adsorbents and membranes for O 2 production processes. The goal of this technology development project was to achieve a bed-factor of less than 600 lb-sorbent/TPD O 2 (tons/day O 2 ) for solid adsorbents, an O 2 /N 2 separation factor greater than 20 for membranes, and O 2 purity greater than 95% at a cost that is projected to be significantly lower than the current state-of-the-art (SOTA) small-scale, commercially available, stand-alone air separation systems. The project team performed a design case for a modular system to produce 10 TPD 95% O 2 and evaluate the cost of O 2 production using such a system.

20 FOSSIL-FUELED POWER PLANTS↗