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All sources NASA NTRS DOE OSTI

DOE OSTI2016

Developing Materials Processing to Performance Modeling Capabilities and the Need for Exascale Computing Architectures (and Beyond)

Additive Manufacturing techniques are presenting the Department of Energy and the NNSA Laboratories with new opportunities to consider novel component production and repair processes, and to manufacture materials with tailored response and optimized performance characteristics. Additive Manufacturing technologies already are being applied to primary NNSA mission areas, including Nuclear Weapons. These mission areas are adapting to these new manufacturing methods, because of potential advantages, such as smaller manufacturing footprints, reduced needs for specialized tooling, an ability to embed sensing, novel part repair options, an ability to accommodate complex geometries, and lighter weight materials. To realize the full potential of Additive Manufacturing as a game-changing technology for the NNSA’s national security missions; however, significant progress must be made in several key technical areas. In addition to advances in engineering design, process optimization and automation, and accelerated feedstock design and manufacture, significant progress must be made in modeling and simulation. First and foremost, a more mature understanding of the process-structure-property-performance relationships must be developed. Because Additive Manufacturing processes change the nature of a material’s structure below the engineering scale, new models are required to predict materials response across the spectrum of relevant length scales, from the atomistic to the continuum. New diagnostics will be required to characterize materials response across these scales. And not just models, but advanced algorithms, next-generation codes, and advanced computer architectures will be required to complement the associated modeling activities. Based on preliminary work in each of these areas, a strong argument for the need for Exascale computing architectures can be made, if a legitimate predictive capability is to be developed.

36 MATERIALS SCIENCE↗

NASA NTRS1980

Orbit Transfer Vehicle (OTV) advanced expander cycle engine point design study. Task 7: Engine data summary

A performance optimized engine system design for a man-rated advanced LOX/hydrogen expander cycle engine was investigated. The data are presented in tables, figures, and drawings. The following categories of data for the advanced expander cycle engine are presented: engine operating specification and pressure schedule; engine system layout drawing; major component layout drawings, including thrust chamber and nozzle, extendible nozzle actuating mechanism and seal, LOX turbopump, LOX boost pump, hydrogen turbopump, hydrogen boost pump, and propellant control valves; engine performance and service life prediction; engine weight; and engine envelope. The data represent updates based upon current results from the design and analyses tasks performed under contract. Futher iterations in the designs and data can be expected as the advanced expander cycle engine design matures.

Christensen, K. L.↗

DOE OSTI2018

Advances in X-ray optics: From metrology characterization to wavefront sensing-based optimization of active optics

Experiments using high brightness X-rays are on the forefront of science due to the vast variety of knowledge they can provide. New Synchrotron Radiation (SR) and Free Electron Laser (FEL) light sources provide unique tools for advanced studies using X-rays. Top-level scientists from around the world are attracted to these beamlines to perform unprecedented experiments. High brightness, low emittance light sources allow beamline scientists the possibility to dream up cutting-edge experimental stations. X-ray optics play a key role in bringing the beam from the source to the experimental stations. This paper explores the recent developments in X-ray optics. It touches on simulations, diagnostics, metrology and adaptive optics, giving an overview of the role X-ray optics have played in the recent past. It will also touch on future developments for one of the most active field in the X-ray science.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Towards Digital and Performance-Based Supervisory HVAC Control Delivery

Upgrading supervisory HVAC control in commercial buildings is one of the most attractive decarbonization tools at our disposal. Modern controls are software programs and can in theory be deployed at scale and with a low up-front carbon "pulse". In practice, however, control delivery is a disjointed and inefficient process, dominated by manual handoffs of imprecise English language documents. A particularly high barrier exists between control implementation and building energy modeling (BEM) which results in control sequences typically not being tested for correctness or performance before implementation. Together with industry partners, DOE and the national labs are developing an ecosystem of tools and standards that can support fully digital performance-based control delivery workflows. This paper describes this ecosystem, which consists of three mutually supportive efforts. Semantic models of buildings and their systems enable automatic configuration and installation of control software. Platform-neutral control descriptions separate control algorithms from control platforms and enable the creation of libraries of reference control implementations. Dynamic whole-building energy-control simulation that can execute physically realistic control sequences makes it possible to test and evaluate the performance of control sequences and then directly compile them for installation and execution in control systems. In addition to digitizing and streamlining project-level control delivery, these standards and related software support benchmarking of control algorithms, both rule-based and optimization-based, and help to both advance the state of the art and to implement ratings and programs that encourage the adoption of high-performance control.

building controls↗

DOE OSTI2023

Quantum Interior Point Methods for Semidefinite Optimization

We present two quantum interior point methods for semidefinite optimization problems, building on recent advances in quantum linear system algorithms. The first scheme, more similar to a classical solution algorithm, computes an inexact search direction and is not guaranteed to explore only feasible points; the second scheme uses a nullspace representation of the Newton linear system to ensure feasibility even with inexact search directions. The second is a novel scheme that might seem impractical in the classical world, but it is well-suited for a hybrid quantum-classical setting. We show that both schemes converge to an optimal solution of the semidefinite optimization problem under standard assumptions. By comparing the theoretical performance of classical and quantum interior point methods with respect to various input parameters, we show that our second scheme obtains a speedup over classical algorithms in terms of the dimension of the problem n , but has worse dependence on other numerical parameters.

Augustino, Brandon↗

DOE OSTI2021

Expanded Capabilities and Opportunities for Virtual Beamline Code

In the 25 years since LLNL broke ground on the National Ignition Facility (NIF) - a cornerstone of the National Nuclear Security Administration’s Stockpile Stewardship Program - the NIF and Photon Science (NIF&PS) Directorate has steadily pushed the boundaries of laser physics, nonlinear optics, and photonics in service of inertial confinement fusion experiments, and advanced photon sources development. Beyond the 192 beamlines of the primary laser facility with its world-record energy and fusion yields, NIF&PS capabilities have expanded to include chirped-pulse amplification, kilojoule petawatt-class short-pulse systems to generate hard x-ray radiographic probes, high-average power lasers as secondary sources for generation or wake field particle acceleration along directed energy applications, and other scientific pursuits. The Computing Directorate partners with NIF&PS on numerous projects and technologies from diagnostic measurements and high performance control systems to data analysis, information technology infrastructure, and scientific simulation code development. “This strong collaboration enables cutting-edge science, particularly with regard to physics-based modeling and simulation,” says physicist Jean-Michel Di Nicola. One crucial capability for NIF&PS is the Virtual Beamline (VBL) laser simulation code. It can model all the major laser physics and technology involved in the design optimization, commissioning, and operations of advanced laser architectures from tabletop to NIF-scale. VBL provides researchers with high-fidelity models and high-resolution calculations of laser performance predictions—including for the entire NIF laser system, the Advanced Radiographic Capability, parts of the High Repetition-Rate Advanced Petawatt Laser System laser delivered to the Czech Republic, and the Optical Science Laser. After more than two decades of experimentally verified physics and computing enhancements, this unique workhorse code is wrapping up another major milestone: migration from Java to C++ with a flurry of user interface and optimization features, as well as laser physics and high-resolution enhancements thanks to parallel execution on Livermore Computing platforms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Optimization of nanosecond transient plasma ignition for clean combustion

Based on a previously developed, retrofittable nanosecond pulsed TPS ignition prototype, transient plasma ignition technology is evaluated for higher energy efficiency and lower emission by optimizing pulse power conditions using advanced diagnostic-based approaches. Combustion performances of a TPS ignition electrode powered by nanosecond voltage pulses of two different rising times (i.e. 4 ns and 8 ns) but the same full-width-half-maximum (FWHM) of 6 ns were compared for single-shot and high-repetition-rate ignitions. The use of faster risetime reduces the voltage amplitude criterion for combustion ignition under a single-shot, stoichiometric fuel-air condition, resulting in higher energy efficiency. In addition, it was demonstrated that high-frequency bursts of pulses positively affect the combustion process; four-consecutive pulsed plasma ignition at a pulse repletion rate (PRR) of 1 kHz needs only half of the voltage to achieve combustion, and increasing the PRR from 1 kHz to 10 kHz improves the energy efficiency by a factor of >1.3. A prototype of retrofittable nanosecond pulsed ignition system was developed and tested in a newly built testing/diagnostic platform, paving the way for ultimate optimization of the TPS prototype for low cost, highly efficient, and low emission combustion.

02 PETROLEUM↗

DOE OSTI2023

Optimizing Irregular Communication with Neighborhood Collectives and Locality-Aware Parallelism

Irregular communication often limits both the performance and scalability of parallel applications. Typically, applications individually implement irregular communication as point-to-point, and any optimizations are integrated directly into the application. As a result, these optimizations lack portability. It is difficult to optimize point-to-point messages within MPI, as the interface for single messages provides no information on the collection of all communication to be performed. However, the persistent neighbor collective API, released in the MPI 4 standard, provides an interface for portable optimizations of irregular communication within MPI libraries. This paper presents methods for implementing existing optimizations for irregular communication within neighborhood collectives, analyzes the impact of replacing point-to-point communication in existing codebases such as Hypre BoomerAMG with neighborhood collectives, and finally shows up to a 1.38x speedup on sparse matrix-vector multiplication communication within a BoomerAMG solve through the use of our optimized neighbor collectives. Here, the authors analyze three implementations of persistent neighborhood collectives for Alltoallv: an unoptimized wrapper of standard point-to-point communication, and two locality-aware aggregating methods. The second locality-aware implementation exposes an non-standard interface to perform additional optimization, and the authors present the additional 0.07x speedup from the extended interface. All optimizations are available in an open-source codebase, MPI Advance, which sits on top of MPI, allowing for optimizations to be added into existing codebases regardless of the system MPI install.

AMG↗

NASA NTRS2016

A Vision and Roadmap for Increasing User Autonomy in Flight Operations in the National Airspace

The purpose of Air Transportation is to move people and cargo safely, efficiently and swiftly to their destinations. The companies and individuals who use aircraft for this purpose, the airspace users, desire to operate their aircraft according to a dynamically optimized business trajectory for their specific mission and operational business model. In current operations, the dynamic optimization of business trajectories is limited by constraints built into operations in the National Airspace System (NAS) for reasons of safety and operational needs of the air navigation service providers. NASA has been developing and testing means to overcome many of these constraints and permit operations to be conducted closer to the airspace user's changing business trajectory as conditions unfold before and during the flight. A roadmap of logical steps progressing toward increased user autonomy is proposed, beginning with NASA's Traffic Aware Strategic Aircrew Requests (TASAR) concept that enables flight crews to make informed, deconflicted flight-optimization requests to air traffic control. These steps include the use of data communications for route change requests and approvals, integration with time-based arrival flow management processes under development by the Federal Aviation Administration (FAA), increased user authority for defining and modifying downstream, strategic portions of the trajectory, and ultimately application of self-separation. This progression takes advantage of existing FAA NextGen programs and RTCA standards development, and it is designed to minimize the number of hardware upgrades required of airspace users to take advantage of these advanced capabilities to achieve dynamically optimized business trajectories in NAS operations. The roadmap is designed to provide operational benefits to first adopters so that investment decisions do not depend upon a large segment of the user community becoming equipped before benefits can be realized. The issues of equipment certification and operational approval of new procedures are addressed in a way that minimizes their impact on the transition by deferring a change in the assignment of separation responsibility until a large body of operational data is available to support the safety case for this change in the last roadmap step.This paper will relate the roadmap steps to ongoing activities to clarify the economics-based transition to these technologies for operational use.

Cotton, William B.↗

DOE OSTI2014

Physics challenges for advanced fuel cycle assessment

Advanced fuel cycles and associated optimized reactor designs will require substantial improvements in key research area to meet new and more challenging requirements. The present paper reviews challenges and issues in the field of reactor and fuel cycle physics. Typical examples are discussed with, in some cases, original results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1984

An optimal control approach to pilot/vehicle analysis and Neal-Smith criteria

The approach of Neal and Smith was merged with the advances in pilot modeling by means of optimal control techniques. While confirming the findings of Neal and Smith, a methodology that explicitly includes the pilot's objective in attitude tracking was developed. More importantly, the method yields the required system bandwidth along with a better pilot model directly applicable to closed-loop analysis of systems in any order.

Bacon, B. J.↗

NASA NTRS1977

Application of numerical optimization to the design of supercritical airfoils without drag-creep

Recent applications of numerical optimization to the design of advanced airfoils for transonic aircraft have shown that low-drag sections can be developed for a given design Mach number without an accompanying drag increase at lower Mach numbers. This is achieved by imposing a constraint on the drag coefficient at an off-design Mach number while the drag at the design Mach number is the objective function. Such a procedure doubles the computation time over that for single design-point problems, but the final result is worth the increased cost of computation. The ability to treat such multiple design-point problems by numerical optimization has been enhanced by the development of improved airfoil shape functions. Such functions permit a considerable increase in the range of profiles attainable during the optimization process.

Hicks, R. M.↗

NASA NTRS2023

Passive Rocket Diffuser Testing: Reacting Flow Performance of Advanced Configurations

Upper stage rocket engines are optimized for operation at the edge of space. Ground testing often requires simulation of high-altitude environments to prevent damage from off-design operation. Passive supersonic diffusers are an effective means of establishing the partial vacuum needed around the nozzle exit. The low cost of diffusers relative to active vacuum sources (ejectors, pumps, etc.) provides a perpetual incentive to improve their performance and expand the envelope of passively testable engines. Second-throat diffusers have been the de facto standard for rocket testing since the 1950s, and numerous studies have focused on parametric optimization of the topology. Yet, even the best second-throat designs may require more driving pressure than an upper stage engine can provide. To overcome conventional limits, engineers at NASA’s Stennis Space Center (SSC) adapted an obscure cold-flow diffuser topology to the extremes of immersion in supersonic combustion products. Aerodynamic experimentation was conducted at SSC’s E-3 test stand to quantify the performance of prototypical hot-fire spike diffuser hardware and enable direct comparison to prior states of the art. A LO X /GH 2 thruster was contoured to approximate the regeneratively-cooled nozzle of an upper-stage engine and fired into 28 downstream diffuser configurations: 16 second-throat, 2 centerbody, and 10 spike. Temperature and pressure were recorded along the test article walls for a range of chamber pressures spanning 3.5 - 5.0 MPa. The second-throat configurations with the lowest start and unstart pressure ratios were shown to outperform equivalent systems in literature and taken as baselines for evaluation of advanced diffuser performance. Compared to these exemplars, centerbody diffusers decreased start pressure ratio by 11% but increased unstart pressure ratio by 15%. Spike diffusers reduced start and unstart pressure ratios by 24% and 9%, respectively.

Rocket↗

DOE OSTI2024

Jacobian-based Model Diagnostics and Application to Equation Oriented Modeling of a Carbon Capture System

Equation-oriented (EO) modeling has the potential to enable the effective design and optimization of the operation of advanced energy systems. However, advanced modeling of energy systems results in a large number of variables and non-linear equations, and it can be difficult to search through these to identify the culprit(s) responsible for convergence issues. The Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES-IP) contains a tool to identify poorly scaled constraints and variables by searching for rows and columns of the Jacobian matrix with small L2-norms so they can be rescaled. A further singular value decomposition can be per-formed to identify degenerate sets of equations and remaining scaling issues. This work presents an EO model of a flowsheet developed for post-combustion carbon capture using a monoethanolamine (MEA) solvent system as a case study. The IDAES diagnostics tools were successfully applied to this flowsheet to identify problems to improve model robustness and enable the optimization of process design and operating conditions of a carbon capture system.

Allan, Douglas↗

DOE OSTI2024

The Compelling Need for a Mid-Scale Stellarator Facility

In the pursuit of the goal of commercial fusion as an abundant and safe source of energy, the stellarator is a leading concept with compelling attractiveness and demonstrated performance. A new mid-size stellarator is needed to retire risks and innovate towards a high performance, economically attractive, stellarator Fusion Pilot Plant. In this presentation we, as a community of US researchers from Universities, National Laboratories, and Private Industry, involved in studying the stellarator concept, lay out the programmatic and technical motivation for a new and modern mid-size stellarator research facility. A new mid-scale stellarator is needed to realize the potential predicted by a solid body of theory and simulation along with advances in computational tools for optimization and non-linear turbulence modeling. Notably, it is possible to combine the advantages of the stellarator (steady state, no current drive, no disruptions) with the good confinement regularly achieved in tokamaks. The top priorities for experimental work, and the motivation for a mid-scale stellarator experiment are: turbulence control, non-resonant divertor, MHD stability at large beta, confinement of fast particles, and coil simplification. A new mid-size quasi-symmetric stellarator, built as a user facility, would complement existing research at Wendelstein 7-X and LHD and strongly augment private industry. It would provide a program of innovative research, concept validation, theoretical advancement, and workforce development. Growing support and interest for stellarators by the fusion community and private industry affirms this rationale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

A resilient network recovery framework against cascading failures with deep graph learning

Because of the increasing importance and dependencies of infrastructure networks and the potential for massive cascading failures in real-world network systems, maintenance optimization to effectively reduce system performance loss caused by diverse disruptions is of significant interest among researchers and practitioners. In this work, a new recovery framework was developed to rapidly identify important system components for maintenance to improve network resilience against cascading failures. Here this work provides distinct advantages to determine an optimal maintenance priority by combining real-time network structure importance with other maintenance prioritization based on customer preference. This approach adopts structural graph embedding and deep reinforcement learning to extract real-time network topology information (such as minimum vertex cover) to update the maintenance priority during the recovery process. Based on the case studies on synthetic networks and a US airport network, the proposed recovery framework with real-time network topology awareness shows better performance than other maintenance prioritization strategies regarding resilience enhancement. This work improves the understanding of how the changing network structure influences maintenance effects. It also provides insights of the practical usefulness of advanced deep learning on helping optimal maintenance prioritization to effectively reduce the intensity and extent of cascading failures.

42 ENGINEERING↗

DOE OSTI2020

Optimizing Asynchronous Multi-Level Checkpoint/Restart Configurations with Machine Learning

With the emergence of versatile storage systems, multi-level checkpointing (MLC) has become a common approach to gain efficiency. However, multi-level checkpoint/restart can cause enormous I/O traffic on HPC systems. To use multilevel checkpointing efficiently, it is important to optimize check-point/restart configurations. Current approaches, namely modeling and simulation, are either inaccurate or slow in determining the optimal configuration for a large scale system. In this paper, we show that machine learning models can be used in combination with accurate simulation to determine the optimal checkpoint configurations. We also demonstrate that more advanced techniques such as neural networks can further improve the performance in optimizing checkpoint configurations.

checkpoint-restart↗

DOE OSTI2018

Development of Optimized Controls and Hardware for Synchrotron Hard X-ray Microscopes with Advanced Spectroscopic Capabilities

The technical objectives of the program were to develop an integrated, fully automated command and data interface between the TXM-Wizard developed at SLAC and the Xradia control software that is used on the Xradia Nano-TXM x-ray microscope with the goal of allowing non-experts including industry users to routinely access the advanced imaging modes that employ collection of images with spectroscopic information. The major accomplishment associated with this goal was the development of a plan to convert the TXM-Wizard software from MatLab to Python and the hiring of an expert Python programmer under contract to perform the conversion.

47 OTHER INSTRUMENTATION↗