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DOE OSTI2024

Intelligent Pixel Detectors: Towards a Radiation Hard ASIC with On-Chip Machine Learning in 28 nm CMOS

Detectors at future high energy colliders will face enormous technical challenges. Disentangling the unprecedented numbers of particles expected in each event will require highly granular silicon pixel detectors with billions of readout channels. With event rates as high as 40 MHz, these detectors will generate petabytes of data per second. To enable discovery within strict bandwidth and latency constraints, future trackers must be capable of fast, power efficient, and radiation hard data-reduction at the source. We are developing a radiation hard readout integrated circuit (ROIC) in 28nm CMOS with on-chip machine learning (ML) for future intelligent pixel detectors. We will show track parameter predictions using a neural network within a single layer of silicon and hardware tests on the first tape-outs produced with TSMC. Preliminary results indicate that reading out featurized clusters from particles above a modest momentum threshold could enable using pixel information at 40 MHz.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Computational Fluid Dynamics Simulations to Support Efficiency Improvements in Aluminum Smelting Process

Smelting is broadly described as the extraction of a metal from its ore. In the United States, aluminum is commonly produced by smelting alumina in bauxite using the Hall-Héroult process. Optimization of equipment and processes in conventional smelting is crucial to enhancing process efficiency and productivity, is necessary for improving the techno-economic feasibility, which directly manifests as the growth of the American economy. To achieve optima, insightful data on the multiphysics phenomena that are inherent to the process must be obtained through physical investigation or high-fidelity numerical simulations. The resolution of relevant scales in time and space for smelting operations requires intensive, high-performance computing (HPC) simulations. Hostile operating conditions limit physical data acquisition to specific techniques; therefore, these data do not describe the multiscale interaction of simultaneous effects. Fortunately, in recent decades, significant advancements in computing hardware and computational methods have made the numerical resolution of such a complex process possible. In this study, a high-fidelity simulation of aluminum smelting was performed using an open-source tool, OpenFOAM, which analyzed many parameters characteristic to underlying phenomena. A multiphysics model based on the Eulerian-Eulerian multifluid approach was adopted. This model can resolve critical issues in the electrolytic smelting of aluminum, such as bubbling of carbon dioxide from the anode(s), magnetohydrodynamics from electromagnetic effects, ionic dissolution of the alumina in the electrolyte, and the evolution of thermal profiles. This study provides valuable connectivity for characteristic data that can direct the future designs of efficient smelters. A basic framework to model and simulate the smelting process using OpenFOAM is presented for user modification in keeping with process development. Of relevance to the flow field, a detailed investigation of vortices produced by bubble motion and electromagnetics is discussed, along with their impact on the evolution of thermal profiles. The predictions show small-scale vortices in the clearance between the anode and cathode caused by magnetic forces. Predictions also indicate relatively large-scale vortices in the inter-anode space resulting from carbon dioxide rising through the electrolytic flow field. The formation of vortices at the edges of anodes was shown to direct alumina charged by the feeder to the bottom of the anodes, thus preventing the entrapment of gas bubbles in the periphery of the bottom of the anode. Symmetry was observed in the location of cold spots in the electrolytic mixture in the vicinity of the feeder. Cold spots were also observed in the clearance between the anode and cathode due to the flow’s transmission of unconverted alumina to this region.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Leveraging National Laboratory Assets to Address Stability Challenges due to Declining Grid Inertia Using Geographically Distributed Electrical–Thermal Co-Emulation

Due to increased penetration of low-inertia resources into the electric grid, challenges are increasing for maintaining wide-area system stability. Grid stability assessment requires a faithful representation of the multiple-physics interaction at the system level, and timescales of interaction varying in orders of magnitude, from microseconds to seconds to several minutes. Along with the simulation-based techniques, hardware-in-the-loop (HIL), controller HIL, and power HIL techniques have been developed to better understand the emergent behavior of the system with emerging technologies. US National Laboratories have played a vital role in research and development to understand the behavior of individual technologies and devices integrated to the electric grid. Each national laboratory forwards a technological and strategic initiative tied core and enabling capabilities. Due to strategic, efficiency, and economic reasons, not all the labs have assets to conduct research on all technologies concomitantly, so it becomes crucial to integrate the labs across geographies to understand the interplay of different technologies together at the system level. This approach avoids duplication of the assets at different lab facilities and helps understand the integrated system behavior of various technologies representative of actual grid conditions by connecting multiple national labs. This article talks about techniques of connecting three national laboratories to enable co-emulation of electrical–mechanical–thermal characteristics of devices and systems. Such an approach can be used to understand the dynamic and transient interaction of multi-physics in a system level, at-scale emulation using real-time simulation tools and techniques.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Capturing the Page curve and entanglement dynamics of black holes in quantum computers

Quantum computers are emerging technologies expected to become important tools for exploring various aspects of fundamental physics in the future. Therefore, we pose the question of whether quantum computers can help us to study the Page curve and the black hole information dynamics, which has been a key focus in fundamental physics. In this regard, we rigorously examine the qubit transport model, a toy qubit model of black hole evaporation on IBM’s superconducting quantum computers, to shed light on this question. Specifically, we implement the quantum simulation of the scrambling dynamics in black holes using an efficient random unitary circuit. Furthermore, we employ the swap-based many-body interference protocol and the randomized measurement protocol to measure the entanglement entropy of Hawking radiation qubits in this model. Finally, by incorporating quantum error mitigation techniques into our challenging implementation of entanglement entropy measurement protocols on the IBM quantum hardware, we accurately determine the Rényi entropy in the qubit transport model, thus showcasing the utility of quantum computers for future investigations of complex quantum systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Online task-space motion control for positioner-coordinated multi-robot manufacturing systems

Incorporating multiple robotic manipulators into large-scale manufacturing systems enhances production efficiency and expands manufacturing capabilities beyond those of single-robot systems. Workpiece positioners in robotic manufacturing have demonstrated significant benefits for process optimization, but coordination strategies for multi-robot systems with shared positioners have received limited attention. This work presents a task-space coordinated trajectory-tracking control framework for multi-robot manufacturing systems, in which robots coordinate their motions within a shared, dynamic workpiece positioning frame. A workpiece positioner actively adjusts the pose of the manufactured component to enable greater operational concurrency and improve overall production efficiency. The proposed motion-coordination scheme employs a distributed and scalable architecture, supporting coordination across heterogeneous multi-robot systems. Two optimization methodologies are introduced to manage kinematic redundancies and maintain continuous, near-optimal operation throughout the manufacturing process. The first strategy exploits a task-space dimensionality reduction to achieve locally optimal configurations by leveraging symmetry-axis rotations of the tool. The second strategy utilizes the workpiece positioner to drive the coordinated robots toward stable and kinematically favorable configurations. For both optimization strategies, multiple objectives are defined to improve key performance metrics, including manipulability, configuration consistency, proximity to mechanical limits, and motion efficiency. Addressing a key limitation of existing coordination approaches, the framework is designed around online setpoint modification, allowing coordinated robots to respond effectively to in-situ process feedback. The proposed control framework is validated using the Robot Operating System (ROS) middleware on a combination of physical and simulated multi-robot system hardware.

Arbogast, Alex [ORNL] (ORCID:0000000154740723)↗

DOE OSTI2020

Correlating AGP on a quantum computer

For variational algorithms on the near term quantum computing hardware, it is highly desirable to use very accurate ansatze with low implementation cost. Recent studies have shown that the antisymmetrized geminal power (AGP) wavefunction can be an excellent starting point for ansatze describing systems with strong pairing correlations, as those occurring in superconductors. In this work, we show how AGP can be efficiently implemented on a quantum computer with circuit depth, number of CNOTs, and number of measurements being linear in system size. Using AGP as the initial reference, we propose and implement a unitary correlator on AGP and benchmark it on the ground state of the pairing Hamiltonian. Furthermore, the results show highly accurate ground state energies in all correlation regimes of this model Hamiltonian.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Then and Now: Improving Software Portability, Productivity, and 100× Performance

The US Exascale Computing Project (ECP) has succeeded in preparing applications to run efficiently on the first reported Exascale supercomputers in the world. To achieve this, it modernized the whole leadership software stack, from libraries to simulation codes. In this article, we contrast selected leadership software before and after ECP. We discuss how sustainable research software development for leadership computing can embrace the conversation with the hardware vendors, the leadership computing facilities, the software community, and the domain scientists who are the application developers and integrators of software products. We elaborate on how software needs to take portability as a central design principle and to benefit from interdependent teams; we also demonstrate how moving to programming languages with high momentum, like modern C++, can help improve the sustainability, interoperability, and performance of research software. Finally, we showcase how cross-institutional efforts can enable algorithm advances that are beyond incremental performance optimization.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations

Publicly available collections of drug-like molecules have grown to comprise tens of billions of compounds due to advances in combinatorial chemistry. Traditional methods for identifying "hit" molecules from a large collection of potential drug-like candidates have relied on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have the major drawback that they require exceptional computing capabilities for even relatively small collections of molecules. Hyperdimensional Computing (HDC) is a recently-proposed learning paradigm that represents data with high-dimension binary vectors; this allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas. We consider existing HDC approaches for molecular property classification and introduce two novel encodings of a commonly-used molecular representation, the extended connectivity fingerprint (ECFP). We show that HDC-based inference methods are as much as 91 times more efficient than traditional machine learning methods, and achieve an acceleration of nearly nine orders of magnitude compared to molecular docking. Our results show that HDC accelerated methods retain competitive accuracy on a number of well-studied tasks such as molecular property predictions using the MoleculeNet dataset, and bind/no-bind activity classification using the DUD-E and LIT-PCBA datasets. Our work thus motivates further investigation into molecular representation learning to develop ultraefficient pre-screening tools.

Jones, William↗

DOE OSTI2025

Geant4 Event Biasing and Fast Simulation

Geant4 offers advanced event biasing techniques to significantly accelerate simulations involving rare events. Various biasing methods, such as leading particle selection, cross-section biasing, radioactive decay enhancement, and bremsstrahlung splitting, enable efficient event sampling, though they require careful handling. Additionally, Geant4 provides a Fast Simulation Interface, allowing the replacement of standard processes in specific region and for selected particles, enabling faster execution or external code integration. Applications of fast simulation include electromagnetic shower modeling in calorimeters, machine learning inference, and offloading tasks to specialized hardware like GPUs, making Geant4 a powerful tool for computationally demanding simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1989

Systolic array processing of the sequential decoding algorithm

A systolic array processing technique is applied to implementing the stack algorithm form of the sequential decoding algorithm. It is shown that sorting, a key function in the stack algorithm, can be efficiently realized by a special type of systolic arrays known as systolic priority queues. Compared to the stack-bucket algorithm, this approach is shown to have the advantages that the decoding always moves along the optimal path, that it has a fast and constant decoding speed and that its simple and regular hardware architecture is suitable for VLSI implementation. Three types of systolic priority queues are discussed: random access scheme, shift register scheme and ripple register scheme. The property of the entries stored in the systolic priority queue is also investigated. The results are applicable to many other basic sorting type problems.

Chang, C. Y.↗

NASA NTRS1993

WetNet: Using SSM/I data interactively for global distribution of tropical rainfall and precipitable water

The research objectives were the following: (1) to use SSM/I to categorize, measure, and parameterize effects of rainfall systems around the globe, especially mesoscale convective systems; (2) to use SSM/I to monitor key components of the global hydrologic cycle, including tropical rainfall and precipitable water, and links to increasing sea surface temperatures; and (3) to assist in the development of efficient methods of exchange of massive satellite data bases and of analysis techniques, especially their use at a university. Numerous tasks have been initiated. First and foremost has been the integration and startup of the WetNet computer system into the TAMU computer network. Scientific activity was infeasible before completion of this activity. Final hardware delivery was not completed until October 1991, after which followed a period of identification and solution of several hardware and software and software problems. Accomplishments representing approximately four months work with the WetNEt system are presented.

Zipser, Edward J.↗

NASA NTRS2009

Fission Surface Power Technology Development Testing at NASA's Early Flight Fission Test Facility

Fission surface power (FSP) systems could be used to provide power anytime, anywhere on the surface of the Moon or Mars. FSP systems could be used at polar locations, at locations away from the poles, or in permanently shaded regions, with excellent performance at all sites. A potential reference 40 kWe option has been devised that is cost-competitive with alternatives while providing more power for less mass anywhere on the lunar surface. The reference FSP system (FSPS) is also readily extensible for use on Mars. At Mars the system would be capable of operating through global dust storms and providing year-round power at any Martian latitude. Under the NASA Exploration Technology Development Program (ETDP), NASA and the Department of Energy (DOE) have begun technology development on Fission Surface Power (FSP). The primary customer for this technology is the NASA Constellation Program which is responsible for the development of surface systems to support human exploration on the moon and Mars. The objectives of the FSP technology project are: 1) Develop FSP concepts that meet expected surface power requirements at reasonable cost with added benefits over other options. 2) Establish a hardware-based technical foundation for FSP design concepts and reduce overall development risk. 3) Reduce the cost uncertainties for FSP and establish greater credibility for flight system cost estimates. 4) Generate the key products to allow Agency decision-makers to consider FSP as a viable option for flight development. To be mass efficient, FSP systems must operate at higher coolant temperatures and use different types of power conversion than typical terrestrial systems. The primary reason is the difficulty in rejecting excess heat to space. Although many options exist, NASA s current reference FSP system uses a fast spectrum, pumped-NaK cooled reactor coupled to a Stirling power conversion subsystem. The reference system uses technology with significant terrestrial heritage while still providing excellent performance on the surface of the moon or Mars. Recent testing at NASA s Early Flight Fission Test Facility (EFF-TF) has helped assess the viability of the reference FSP system, and has helped evaluate methods for system integration. In June, 2009, a representative pumped NaK loop (provided by Marshall Space Flight Center) was coupled to a Stirling power converter (provided by Glenn Research Center) and tested at various conditions representative of those that would be seen during actual FSP system operation. In all areas, performance of the integrated system exceeded project goals. High-temperature NaK pump testing has also been performed at the EFF-TF, as has testing of methods for providing long-duration NaK purity.

Houts. Michael G.↗

NASA NTRS1991

Combinatorial FSK modulation for power-efficient high-rate communications

Deep-space and satellite communications systems must be capable of conveying high-rate data accurately with low transmitter power, often through dispersive channels. A class of noncoherent Combinatorial Frequency Shift Keying (CFSK) modulation schemes is investigated which address these needs. The bit error rate performance of this class of modulation formats is analyzed and compared to the more traditional modulation types. Candidate modulator, demodulator, and digital signal processing (DSP) hardware structures are examined in detail. System-level issues are also discussed.

Wagner, Paul K.↗

NASA NTRS1991

Combinatorial FSK modulation for power-efficient high-rate communications

Wagner, Paul K.↗

DOE OSTI2024

Precise Motion Control of Hybrid Hydraulic Electric Architecture (HHEA)

Off-highway heavy-duty vehicles have been long-standing users of hydraulic systems for power transmission and control. However, traditional hydraulic systems suffer from significant energy losses which lead to increased operating costs and a larger carbon footprint due to higher CO2 emissions. Improving the efficiency of these mobile machines is crucial not only for reducing their environmental impact but also for saving billions of dollars in operating costs. Currently, the state-of-the-art Load Sensing Architecture uses throttling valves for control, which significantly reduces its efficiency and does not recuperate energy from over-running loads. Researchers have developed several architectures such as Common Pressure Rail systems, Displacement Control, STEAM, and Electrohydraulic Architecture to improve the efficiency of off-road mobile machines. However, each of these architectures has its drawbacks. To increase system efficiency and take advantage of electrification benefits, our research group has developed a novel Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA can significantly improve efficiency, decrease the size of electrical components, and maintain control performance. This new architecture has the potential to revolutionize the off-highway mobile machine industry and lead to a more sustainable future. The HHEA uses a set of common pressure rails to provide the majority of power to the actuators via power-dense hydraulics and uses electric motors for precise control and power modulation. In the context of off-road mobile machines, energy savings are undoubtedly important but it is equally important to consider the machines’ ability to perform tasks with precision and accuracy according to given commands. Therefore, precise motion control is of utmost importance to maintain the utility of Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA presents a unique challenge to motion control due to the discrete pressure changes that occur when the system switches between selected pressure rails. These changes are made to minimize system inefficiencies or to keep the system within the torque capability of the electric motor. Hence, it is important to solve the motion control challenges for HHEA. This thesis aims at developing an effective motion control strategy for HHEA. The dissertation presents a two-tiered control strategy for HHEA, comprising a high-level and a low-level controller. The primary responsibility of the high- level controller is to optimize energy efficiency by making informed pressure rail selections. On the other hand, the low-level controller is focused on achieving precise motion control of the HHEA, which is crucial for realizing the desired reference trajectories. To achieve this, the low-level controller utilizes a passivity-based backstepping integral controller as the nominal control, which handles the motion control between two pressure rail switches. Additionally, a separate least norm controller is utilized as a transition controller to manage motion control during pressure rail transitions. The effectiveness of the combined control strategy is demonstrated through experiments conducted on two hardware-in-the-loop testbeds. Furthermore, the HHEA is installed on the boom and stick actuators of a backhoe arm to build a Human-in-the-Loop system that a human operator can control. A real-time rail switching algorithm is developed to determine pressure rail switching based on present duty cycle information from the operator. Modifications have been made to the human-machine interface to achieve more intuitive control. Modifications include performing control in the task-oriented coordinates, incorporating pressure feedback to enhance control with physical interaction, and using velocity field control to simplify multi-degree-of-freedom tasks and to enable novice operators to perform them with reduced risk, improved efficiency, and productivity. The research in this dissertation makes significant contributions to the field of off-road mobile machine control, providing a novel and effective control strategy for the HHEA, and demonstrating the potential for simplified machine operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Qumode transfer between continuous- and discrete-variable devices

Transferring quantum information between different types of quantum hardware is crucial for integrated quantum technology. In particular, converting information between continuous variable (CV) and discrete variable (DV) devices enables many applications in quantum networking, quantum sensing, quantum machine learning, and quantum computing. This paper addresses the transfer of CV-encoded information between CV and DV devices. We present a resource-efficient method for encoding CV states and implementing CV gates on DV devices, as well as two measurement-based protocols for transferring CV states between CV and DV devices. The success probability of the transfer protocols depends on the measurement outcome and can be increased to near-deterministic values by adding ancillary qubits to the DV devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1980

The software system development for the TAMU real-time fan beam scatterometer data processors

A software package was designed and written to process in real-time any one quadrature channel pair of radar scatterometer signals form the NASA L- or C-Band radar scatterometer systems. The software was successfully tested in the C-Band processor breadboard hardware using recorded radar and NERDAS (NASA Earth Resources Data Annotation System) signals as the input data sources. The processor development program and the overall processor theory of operation and design are described. The real-time processor software system is documented and the results of the laboratory software tests, and recommendations for the efficient application of the data processing capabilities are presented.

Clark, B. V.↗

NASA NTRS1992

High-speed civil transport flight- and propulsion-control technological issues

Technology advances required in the flight and propulsion control system disciplines to develop a high speed civil transport (HSCT) are identified. The mission and requirements of the transport and major flight and propulsion control technology issues are discussed. Each issue is ranked and, for each issue, a plan for technology readiness is given. Certain features are unique and dominate control system design. These features include the high temperature environment, large flexible aircraft, control-configured empennage, minimizing control margins, and high availability and excellent maintainability. The failure to resolve most high-priority issues can prevent the transport from achieving its goals. The flow-time for hardware may require stimulus, since market forces may be insufficient to ensure timely production. Flight and propulsion control technology will contribute to takeoff gross weight reduction. Similar technology advances are necessary also to ensure flight safety for the transport. The certification basis of the HSCT must be negotiated between airplane manufacturers and government regulators. Efficient, quality design of the transport will require an integrated set of design tools that support the entire engineering design team.

Ray, J. K.↗