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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 127 records · Page 7

A Digital Three Level Space Vector Modulator for High Frequency Vector Sequence Generation

This letter proposes a digital high-speed three-level space vector pulse width modulator (3L-SVPWM). A conventional 3L-SVPWM is typically computation-based, involving a sequential execution of sub-tasks on a digital signal processor (DSP) based controller. The resulting high computation time of 5.4 μs limits the implementation of additional control blocks for switching frequencies greater than 100 kHz. This is overcome by transforming sub-tasks into digital blocks with 1-0 decisions and simpler arithmetic operations. The sub-task blocks are executed concurrently on a programmable logic device (PLD). Hence, a fast 3L-SVPWM execution in 140 ns is achieved. The proposed digital 3L-SVPWM enables high switching frequency operation of wide bandgap (WBG) device-based 3 L inverters to generate high fundamental frequency waveforms. A finite state machine is an integral part of the proposed implementation with the ability to generate any vector sequence, maximizing the usage of redundant vector states in 3L-SVPWM. Here, the proposed digital 3L-SVPWM operation is demonstrated with a GaN-based 3 L active neutral point clamped (3L-ANPC) inverter. Experimental results are presented at 250 kHz switching frequency to generate vector sequences for center-aligned SVPWM (CA-SVPWM) and common mode voltage reduced SVPWM (CMVR-SVPWM). The results also showcase a high fundamental frequency generation capability of 10 kHz.

active neutral point clamped inverter↗

Risk-based System Upgrade Planning for AOT-IC Presentation [Slides]

The number of deployed systems and different HW/SW form factors makes it difficult to maintain a complete understanding of their health which leads to a reduced level of certainty when assessing risk and trying to prioritize system upgrade efforts. AOT-IC must constantly plan and execute system upgrade and replacement projects to ensure the longevity of the control system. There are many more projects needed than the group can realistically accomplish given schedule and resource constraints. The group must prioritize their upgrade projects to choose only the highest priority projects to execute each year. Currently plans upgrade and replacement projects based on alignment with mission needs, group vision, resource availability, and qualitative risk assessments based on SME estimates. The group maintains a risk register. This is useful as a tool for shaping strategic planning but currently lacks the quantitative data and process needed to generate accurate risk assessments.

43 PARTICLE ACCELERATORS↗

Subfemtosecond Wakefield Injector and Accelerator Based on an Undulating Plasma Bubble Controlled by a Laser Phase

Here, we demonstrate that a long-propagating plasma bubble executing undulatory motion can be produced in the wake of two copropagating laser pulses: a near-single-cycle injector and a multicycle driver. When the undulation amplitude exceeds the analytically derived threshold, highly localized injections of plasma electrons into the bubble are followed by their long-distance acceleration. While the locations of the injection regions are controlled by the carrier-envelope phase (CEP) of the injector pulse, the monoenergetic spectrum of the accelerated subfemtosecond high-charge electron bunches is shown to be nearly CEP independent.

43 PARTICLE ACCELERATORS↗

Modification of Jet Velocities in an Explosively Loaded Copper Target with a Conical Cavity

Here, in this work, the design and execution of an experiment with the goal of demonstrating control over the evolution of a copper jet is described. Simulations show that when using simple multi-material buffers placed between a copper target with a conical cavity and a cylinder of high-explosive, a variety of jetting behaviors occur based on material placement, including both jet velocity augmentation and mitigation. A parameter sweep was performed to determine optimal buffer designs in two configurations. Experiments using the optimal buffer designs verified the effectiveness of the buffers at altering jet velocities. Similar trends were shown between the experimental results and the modeling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Deploying Automation Technology Supporting Packaging and Transportation Operations

Various United States Department of Energy (DOE) sites are investigating the deployment of robotics to provide safer, effective, and more efficient operations. By implementing robotics in packaging and transportation operations, improvements toward production efficiency, worker ergonomics, radiological dose reduction, and security assurance can be realized. Robotic Systems must be designed and implemented in concert with a facility’s safety basis, classification, and security constraints, while improving overall operational effectiveness. The desired robotic implementation should provide a path to potential long-term cost savings, reduce/eliminate hazardous conditions and radiological exposure, while improving quality and reliability of an operation process. The Savannah River Site (SRS), a DOE Site located in Aiken South Carolina, has initiated several large scale projects supporting future nuclear material disposition activities. Incorporation of automation and robotic equipment in system designs will support effective and efficient material handling operations, including container movements and packaging activities. Robotic systems will execute tasks that are precise, procedural and integrated with control systems to verify and record data for material inventory and historical archiving. An overview of the current robotic system development to perform receipt inspection, packaging, storage and shipment preparation activities of designated Type A and B shipping packages will be presented.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Precursor Analysis Report: Cyber Attack on Thyssenkrupp Blast Furnace 2014

The Cyber Attack on Thyssenkrupp Blast Furnace 2014 Precursor Analysis Report leverages publicly available information about the Thyssenkrupp Steel Mill cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. In December 2014, the German Government’s Federal Office for Information Security (BSI) released a report detailing a cyber attack on a German steel mill that occurred earlier that year, though exact dates and details of the attack were not revealed. While the report did not specify the name of the company, multiple sources identified the victim as one of Europe’s largest steel manufacturers, Thyssenkrupp AG. Further, Thyssenkrupp announced on 16 May of that year that Europe’s largest blast furnace, “Schwelgern 2,” located at its facility in Duisburg, Germany, would be offline for several weeks for repairs and upgrades, suggesting Schwelgern 2 was likely the target of the attack. The attack began in early 2014, when adversaries infiltrated the victim steel mill’s Information Technology (IT) network via a spearphishing campaign, then worked their way into the Operational Technology (OT) environment, where they executed software that caused denial of service, denial of control, and eventually a loss of control. This led to the blast furnace shutting down without proper safety procedures, resulting in catastrophic physical damage. No lives were lost in the incident, but ThyssenKrupp suffered $4 million in damage to the blast furnace and an additional $6 million in lost revenue. The adversaries required specialized knowledge and expertise in steel production, which enabled them to compromise a variety of internal systems and components across both IT and OT networks. The attack also demonstrated detailed knowledge of the industrial control systems (ICS) and production processes being used. This combination resulted in one of the earliest known publicly reported cybersecurity incidents resulting in physical damage to ICS equipment. Researchers and analysts identified 19 unique techniques (used in a sequence of 20 steps) utilized during the attack with a total of 454 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Fifteen of the identified techniques used during the Thyssenkrupp cyber attack were precursors to the triggering event. Analysis identified 369 observables associated with these precursor techniques, 316 of which were assessed to have an increased likelihood of being perceived in the 120 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Computational capacity in hydrodynamic real-time hybrid simulation applied to simulate the dynamic response of floating offshore wind turbines

Real-time hybrid simulation (RTHS) mitigates similitude distortions in model-scale tests of floating offshore wind turbines (FOWTs) by coupling physical experiments with numerical models in real time. The coupling requires faster-than-real-time numerical computations to satisfy temporal similitude with the physical experiment, presenting a bottleneck for using more complex numerical models in RTHS. This paper presents a hydrodynamic-RTHS (hydro-RTHS) framework for FOWTs that simulates the hydrodynamics physically and the aerodynamics numerically with sensor feedback from the physical testing. The framework adapts the three-loop hardware architecture to leverage greater computational resources and mitigate strict temporal requirements, enabling more computationally demanding numerical analyses in hydro-RTHS. The three-loop hardware architecture integrates multiple machines, each dedicated to either numerical analysis or RTHS controls, with a rate-transition algorithm to synchronize the tasks executed across the different machine processors. Virtual and physical tests verified and validated the hydro-RTHS framework, respectively. The ”virtual” tests, which approximates the physical domain numerically, verified the RTHS framework with respect to a numerical full-scale complete FOWT model simulated in the open-source software, OpenFAST. The virtual tests were able to maintain comparable control signals while enabling greater computational resources for the numerical calculations. Real-world physical tests demonstrated that the hydro-RTHS framework computes aerodynamic forces similar to the complete OpenFAST model, validating the hydro-RTHS framework using the three-loop hardware architecture. Findings show that the hydro-RTHS framework with the three-loop hardware architecture is computationally efficient, with reserve capacity to simulate more complex problems due to the customized software, hardware, and rate-transition algorithm.

17 WIND ENERGY↗

Controlling accesses to a branch prediction unit for sequences of fetch groups

An electronic device handles accesses of a branch prediction functional block when executing instructions in program code. The electronic device includes a processor having the branch prediction functional block that provides branch prediction information for control transfer instructions (CTIs) in the program code and a minimum predictor use (MPU) functional block. The MPU functional block determines, based on a record associated with a given fetch group of instructions, that a specified number of subsequent fetch groups of instructions that were previously determined to include no CTIs or conditional CTIs that were not taken are to be fetched for execution in sequence following the given fetch group. The MPU functional block then, when each of the specified number of the subsequent fetch groups is fetched and prepared for execution, prevents corresponding accesses of the branch prediction functional block for acquiring branch prediction information for instructions in that subsequent fetch group.

Agrawal, Varun↗

Extending XACC for Quantum Optimal Control

Quantum computing vendors are beginning to open up application programming interfaces for direct pulse-level quantum control. With this, programmers can begin to describe quantum kernels of execution via sequences of arbitrary pulse shapes. This opens new avenues of research and development with regards to smart quantum compilation routines that enable direct translation of higher-level digital assembly representations to these native pulse instructions. In this work, we present an extension to the XACC system-level quantum-classical software framework that directly enables this compilation lowering phase via user-specified quantum optimal control techniques. This extension enables the translation of digital quantum circuit representations to equivalent pulse sequences that are optimal with respect to the backend system dynamics. Our work is modular and extensible, enabling third party optimal control techniques and strategies in both C++ and Python. We demonstrate this extension with familiar gradient-based methods like gradient ascent pulse engineering (GRAPE), gradient optimization of analytic controls (GOAT), and Krotov's method. Our work serves as a foundational component of future quantum-classical compiler designs that lower high-level programmatic representations to low-level machine instructions.

Nguyen, Thien↗

Quantum-classical tradeoffs and multi-controlled quantum gate decompositions in variational algorithms

The computational capabilities of near-term quantum computers are limited by the noisy execution of gate operations and a limited number of physical qubits. Hybrid variational algorithms are well-suited to near-term quantum devices because they allow for a wide range of tradeoffs between the amount of quantum and classical resources used to solve a problem. This paper investigates tradeoffs available at both the algorithmic and hardware levels by studying a specific case – applying the Quantum Approximate Optimization Algorithm (QAOA) to instances of the Maximum Independent Set (MIS) problem. We consider three variants of the QAOA which offer different tradeoffs at the algorithmic level in terms of their required number of classical parameters, quantum gates, and iterations of classical optimization needed. Since MIS is a constrained combinatorial optimization problem, the QAOA must respect the problem constraints. This can be accomplished by using many multi-controlled gate operations which must be decomposed into gates executable by the target hardware. We study the tradeoffs available at this hardware level, combining the gate fidelities and decomposition efficiencies of different native gate sets into a single metric called the gate decomposition cost .

Tomesh, Teague↗

Driving Next-Generation Workflows from the Data Plane

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

Suter, Fred↗

IMG Annotation Pipeline (IMGAP) v5.1.13

The IMG Annotation Pipeline is a collection of Bash and Python scripts to control a workflow for structural and functional annotation of prokaryotic genomes, metagenomes, and metatranscriptomes. The bash scripts in general control the overall workflow and are wrappers around 3rd party executables (not included in repo) that predict features or functions. Whereas the Python scripts do post-processing of raw output in terms of filtering or format transformation and in some cases contain some logic for picking the correct predictions or resolving overlaps. The pipeline is tailored to produce results required by IMG (https://img.jgi.doe.gov/) and is executed on every dataset submitted to IMG via https://img.jgi.doe.gov/submit. These consist of internal genomes, metagenomes and metatranscriptomes sequenced and assembled at the JGI, as well as datasets submitted by external users (non-lab/JGI affiliates).

Huntemann, Marcel↗

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

Lightfall v0.0.1

Lightfall is a desktop application for synchrotron beamline instrument control, data acquisition, and live analysis at the Advanced Light Source (ALS). Built on Python and Qt, it provides a native graphical interface for operating beamline hardware, configuring and executing experimental scans, and visualizing results in real time. Key features include direct integration with EPICS control systems, a built-in electronic logbook, remote beamline access over secure tunnels, and an interprocess communication (IPC) architecture that coordinates with external analysis applications via ZMQ and EPICS process variables. This IPC approach allows Lightfall to orchestrate specialized analysis tools—including GPU-accelerated streaming correlators—without embedding them, avoiding the dependency conflicts common in monolithic scientific software platforms. Compared to prior approaches such as Xi-CAM's plugin-based architecture, Lightfall's design cleanly separates instrument control from domain-specific analysis, enabling feedback-driven acquisition where live analysis results can adjust scan parameters during an experiment. Its native Qt interface provides responsive performance for real-time data visualization that web-based alternatives struggle to match. Lightfall is designed for use by beamline scientists and staff operating synchrotron instruments at national user facilities.

Pandolfi, Ronald [Lawrence Berkeley National Labor↗

Instructions for performing multi-line memory accesses

A system is described that performs memory access operations. The system includes a processor in a first node, a memory in a second node, a communication interconnect coupled to the processor and the memory, and an interconnect controller in the first node coupled between the processor and the communication interconnect. Upon executing a multi-line memory access instruction, the processor prepares a memory access operation for accessing, in the memory, a block of data including at least some of each of at least two lines of data. The processor then causes the interconnect controller to use a single remote direct memory access memory transfer to perform the memory access operation for the block of data via the communication interconnect.

Roberts, David A.↗

Power Hardware-In-the-Loop Hydropower and Ultracapacitor Hybrid Testbed

Widespread deployment of a proof-of-concept technological solution for power system performance improvement can be accelerated through onsite demonstration and pilot projects. Digital real-time simulation with power hardware-in-the-loop in controlled lab environment is the precursor to de-risk the timely and efficient execution of field demonstration and pilot projects. However, the detailed process of development, characterization, and calibration of such high fidelity simulation testbed needs to be documented in a reproducible and publicly accessible manner to leverage across broader research and development communities. This paper presents such a laboratory testbed to study black start capability of a run-of-river hydro + ultracapacitor hybrid system. Beside the high-fidelity model of the islanded grid with hydropower unit, the testbed includes the energy storage, grid following inverter, and grid emulator hardware. Several aspects such as storage characterization, control and various parameter settings necessary to capture frequency transients during load restoration are described in a comprehensive manner, which led to an effective and timely execution of black start field demonstration with an actual hydropower plant.

13 HYDRO ENERGY↗

The Case for Co-Designing Model Architectures with Hardware

While GPUs are responsible for training the vast majority of state-of-the-art deep learning models, the implications of their architecture are often overlooked when designing new deep learning (DL) models. As a consequence, modifying a DL model to be more amenable to the target hardware can significantly improve the runtime performance of DL training and inference. In this paper, we provide a set of guidelines for users to maximize the runtime performance of their transformer models. These guidelines have been created by carefully considering the impact of various model hyperparameters controlling model shape on the efficiency of the underlying computation kernels executed on the GPU. We find the throughput of models with “efficient” model shapes is up to 39% higher while preserving accuracy compared to models with a similar number of parameters but with unoptimized shapes.

Yin, Junqi↗

Optvis

Optvis is a web application to visualize control flow graphs, call graphs, disassembly code from a binary or executable. The main use case is visualizing the compiler optimizations in binary code.

Aschwanden, PascalD.↗