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At least 775 records · Page 43

Accelerated Creep Test Qualification of Creep-Resistance Using the Wilshire–Cano–Stewart Constitutive Model and Stepped Isostress Method

In this paper, a qualification of accelerated creep-resistance of Inconel 718 is assessed using the novel Wilshire–Cano–Stewart (WCS) model and the stepped isostress method (SSM) and predictions are made to conventional creep data. Conventional creep testing is a long-term continuous process; in fact, the ASME B&PV III requires that 10,000+ h of experiments must be conducted to each heat for materials employed in boilers and/or pressure vessel components. This process is costly and not feasible for rapid development of new materials. As an alternative, accelerated creep testing techniques have been developed to reduce the time needed to characterize the creep resistance of materials. Most techniques are based upon the time-temperature-stress superposition principle that predicts minimum-creep-strain-rate (MCSR) and stress-rupture behaviors but lack the ability to predict creep deformation and consider deformation mechanisms that occur for experiments of longer duration. The SSM has been developed, which enables the prediction of creep deformation response as well as reduce the time needed for qualification of materials. The SSM approach has been successful for polymer, polymeric composites, and recently has been introduced for metals. In this study, the WCS constitutive model, calibrated to SSM test data, qualifies the creep resistance of Inconel 718 at 750 °C and predictions are compared to conventional creep testing data. The WCS model has proven to make long-term predictions for stress-rupture, MCSR, creep deformation, and damage in metallic materials. The SSM varies stress levels after time interval adding damage to the material, which can be tracked by the WCS model. The SSM data is calibrated into the model and the WCS model generates realistic predictions of stress-rupture, MSCR, damage, and creep deformation. The calibrated material constants are used to generate predictions of stress-rupture and are postaudit validated using the National Institute of Material Science database. Similarly, the MCSR predictions are compared from previous studies. Finally, the creep deformation predictions are compared with real data and is determined that the results are well in between the expected boundaries. Material characterization and mechanical properties can be determined at a faster rate and with a more cost-effective method. This is beneficial for multiple applications such as in additive manufacturing, composites, spacecraft, and industrial gas turbines.

42 ENGINEERING↗

Through the lens of bioenergy crops: advances, bottlenecks, and promises of plant engineering

Advances in engineering of bioenergy crops were driven over the past years by adapting technological breakthroughs and accelerating conventional applications but also exposed intriguing challenges. New tools revealed rich interconnectivity in the exponentially growing and dynamic 'big' omics data' of metabolomes, transcriptomes, and genomes at previously inaccessible magnitude (global, cross-species, meta-) and resolution (single cell). Insights enabled fresh hypotheses and stimulated disciplines such as functional genomics with discovery of broad regulatory networks and their determinants, that is, DNA parts, including promoters, regulatory elements, and transcription factors. Their rational design, assembly into increasingly complex blueprints, and installation into diverse chassis is an existing frontier that may benefit from emerging technologies to address bottlenecks. Interweaving nature-inspired to fully synthetic parts has already allowed building of fine-tuned regulatory circuits, or new-to-nature metabolic routes insulated from the biological context of the chassis species. Similarly, developments and the evolving need for unifying principles in plant transformation and species-agnostic technologies highlight future opportunities for engineering the next generation of bioenergy plants.

60 APPLIED LIFE SCIENCES↗

Influence of substitution pattern on the dynamics of internal conversion and intersystem crossing in thiopyridone isomers

We report a combined experimental and theoretical investigation of the ultrafast internal conversion (IC) and intersystem crossing (ISC) dynamics of two thiopyridone (TP) isomers in solution. Our study used ultrafast transient X-ray absorption spectroscopy (XAS) at the sulfur K-edge, in conjunction with electronic excited state surface hopping molecular dynamics and simulations of the excited state XAS, to investigate the impact of the functional group substitution pattern and solvent on the dynamics of IC and ISC. The combination of the localized X-ray probe and the simulation results enables, in part, the differentiation between ππ* and nπ* character excited states, as well as singlet and triplet states. Access to nπ* character excitations has particular value since they often prove challenging to assess with optical spectroscopy. For 2-TP, the photoexcited S 2 (ππ*) state rapidly undergoes IC to the S 1 (nπ*) state below the instrument response time, followed by ISC to the T 1 (ππ*) state on a timescale of 600 fs in acetonitrile. For 4-TP, the timescale of S 2 to S 1 IC increases to 330 fs and the timescale of ISC increases to more than 10 ps. The differences between isomers are rationalized by considering the key role of the, nπ* intermediates in mediating the intersystem crossing of these systems. Varying the substitution pattern of the molecule can stabilize or destabilize these intermediates leading to the increase in ISC rate in the ortho isomer as compared to the para isomer, while changing the solvent from acetonitrile to water had minimal effect on the electronic excited state relaxation mechanism.

Garratt, Douglas [SLAC National Accelerator Labora↗

Optical neural engine for solving scientific partial differential equations

Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.

Tang, Yingheng (ORCID:0009000153622546)↗

Towards standardized nuclear reactors: Seismic isolation and the cost impact of the earthquake load case

We report nuclear energy has a key role to play in global decarbonization. Impediments to the widespread deployment of reactors are their projected high capital cost and levelized cost of energy, and time required to analyze, design, license, construct, and commission them. The earthquake load case is a key cost driver for a new build nuclear plant, because near-surface soils and seismic hazard are different at each site, requiring site-specific analysis, design, engineering, qualification, licensing, and regulatory review, essentially making every design First-of-a-Kind (FoaK). To enable deployment at the scale needed for deep decarbonization, the cost and time impact of the seismic load case must be significantly mitigated, and plants must be standardized. Seismic base isolation has been proven to considerably reduce the earthquake response of structures and equipment but has yet to be applied to a nuclear power plant in the United States, in part because the financial impacts, positive or negative, are not known. Because there are no recent non-proprietary data to characterize the influence of the seismic load case on capital cost, it is difficult to confidently quantify the financial benefits of seismic isolation. Scheme-level designs of two fundamentally different advanced reactor buildings were developed to assemble cost data on the influence of the seismic load case. Both buildings were equipped with three bespoke pieces of safety-related equipment and analyzed for incremented levels of earthquake shaking to quantify the seismic penalty on equipment, in terms of vessel weights and horizontal accelerations. Using analysis results, a questionnaire was developed and transmitted to nuclear utilities, reactor developers, engineers, and equipment suppliers to collect cost data on engineering and fabrication costs for these unique pieces of safety-class equipment. Synthesis of the cost data showed that the seismic load case significantly affects the capital cost (sum of engineering and fabrication cost) of safety-class equipment, with engineering costs being comparable to fabrication costs. Standardization of safety-class equipment is made possible by seismic isolation, that is, equipment designed for minimal seismic robustness can resist earthquake shaking at a site of much higher seismic hazard. The average reduction in the capital cost of the safety-related equipment, enabled by seismic isolation, is a factor of two for FoaK equipment and a factor of five for standardized equipment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Orbit-on-demand vehicle propelled by air-turborocket/ramjet engines

A preliminary design study has been completed for a fully reusable, single-stage-to-orbit transatmospheric vehicle. The specified mission capability was to lift a 20,000 lb payload to low earth orbit. A ground accelerator-assisted horizontal take-off was chosen to increase operational flexibility. The multi-mode propulsion system included the use of air-turborocket, ramjet, scramjet and rocket engines. Weight and performance estimates were obtained for the vehicle. A computer package was developed to perform aerothermodynamic analyses of the propulsion modes throughout the flight environment from take-off to low earth orbit. Results are presented for a semi-optimized trajectory. The analysis indicates that a vehicle of this type has great potential for providing low cost, flexible access to space.

Hartung, L.↗

White Paper on Nuclear Astrophysics and Low Energy Nuclear Physics Part 1: Nuclear Astrophysics

This white paper informs the nuclear astrophysics community and funding agencies about the scientific directions and priorities of the field and provides input from this community for the 2015 Nuclear Science Long Range Plan. It summarizes the outcome of the nuclear astrophysics town meeting that was held on August 21-23, 2014 in College Station at the campus of Texas AM University in preparation of the NSAC Nuclear Science Long Range Plan. It also reflects the outcome of an earlier town meeting of the nuclear astrophysics community organized by the Joint Institute for Nuclear Astrophysics (JINA) on October 9-10, 2012 Detroit, Michigan, with the purpose of developing a vision for nuclear astrophysics in light of the recent NRC decadal surveys in nuclear physics (NP2010) and astronomy (ASTRO2010). The white paper is furthermore informed by the town meeting of the Association of Research at University Nuclear Accelerators (ARUNA) that took place at the University of Notre Dame on June 12-13, 2014. In summary we find that nuclear astrophysics is a modern and vibrant field addressing fundamental science questions at the intersection of nuclear physics and astrophysics. These questions relate to the origin of the elements, the nuclear engines that drive life and death of stars, and the properties of dense matter. A broad range of nuclear accelerator facilities, astronomical observatories, theory efforts, and computational capabilities are needed. With the developments outlined in this white paper, answers to long standing key questions are well within reach in the coming decade.

Nuclear astrophysics; White paper; Nucleosynthesis↗

CFD-Guided Combustion System Optimization of a Gasoline Range Fuel in a Heavy-Duty Compression Ignition Engine Using Automatic Piston Geometry Generation and a Supercomputer

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty diesel engine running with a gasoline fuel that has a research octane number (RON) of 80. The goal was to optimize the gasoline compression ignition (GCI) combustion recipe (piston bowl geometry, injector spray pattern, in-cylinder swirl motion, and thermal boundary conditions) for improved fuel efficiency while maintaining engine-out NO x within a 1-1.5 g/kW-hr window. The numerical model was developed using the multi-dimensional CFD software CONVERGE. A two-stage design of experiments (DoE) approach was employed with the first stage focusing on the piston bowl shape optimization and the second addressing refinement of the combustion recipe. For optimizing the piston bowl geometry, a software tool, CAESES, was utilized to automatically perturb key bowl design parameters. This led to the generation of 256 combustion chamber designs evaluated at several engine operating conditions. The second DoE campaign was conducted to optimize injector spray patterns, fuel injection strategies and in-cylinder swirl motion for the best performing piston bowl designs from the first DoE campaign. This comprehensive optimization study was performed on a supercomputer, Mira, to accelerate the development of an optimized fuel-efficiency focused design. Compared to the production combustion system in the baseline engine, the new combustion recipe from this study showed significantly improved closed-cycle fuel efficiency across key engine operating points while meeting the engine-out NO x targets. Optimized piston bowl designs and injector spray patterns were predicted to provide enhanced in-cylinder air utilization and more rapid mixing-controlled combustion, thereby leading to a fuel efficiency improvement. In addition, shifting the engine thermal boundary conditions toward leaner operation was also key to the improved fuel efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

Experimental Investigation of an Overriding Control to Effect Recovery from Surge and Stall in a Turbojet Engine

The override was designed to automatically recover the engine from stall and surge by reducing fuel flow and then increasing fuel flow in a manner to avoid repeated stalls and surges and successfully complete the acceleration. One of two parameters was used to operate the override, tailpipe temperature, or the derivative of compressor-discharge pressure. The override operating with tailpipe temperature recovered the engine from stall and surge. Operating on compressor-discharge-pressure derivative, the override recovered the engine from surge, but failed when stall was encountered.

Stiglic, Paul M↗

Floquet-engineered fast SNAP gates in weakly coupled circuit-QED systems

Superconducting cavities with high quality factors, coupled to a fixed-frequency transmon, provide a state-of-the-art platform for quantum information storage and manipulation. The commonly used selective number-dependent arbitrary phase ( SNAP ) gate faces significant challenges in ultrahigh-coherence cavities, where the weak dispersive shifts necessary for preserving high coherence typically result in prolonged gate times. Here, in this work, we propose a protocol to achieve high-fidelity SNAP gates that are orders of magnitude faster than the standard implementation, surpassing the speed limit set by the bare dispersive shift. We achieve this enhancement by dynamically amplifying the dispersive coupling via sideband interactions, followed by quantum optimal control on the Floquet-engineered system. We also present a unified perturbation theory that explains both the gate acceleration and the associated benign drive-induced decoherence, corroborated by Floquet-Markov simulations. These results pave the way for the experimental realization of high-fidelity, selective control of weakly coupled, high-coherence cavities, and expanding the scope of optimal control techniques to a broader class of Floquet quantum systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Spiking Markov Reward Process v.0.1

SAND2024-11150O The Spiking Markov Reward Process software is a spiking neural network that streams binary arithmetic and computes the state value function of a Markov reward process. The software will be released to the SpiNNcloud group for development of neuromorphic acceleration. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Wang, Felix↗

Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗

Fast and High-Fidelity SNAP Gate Enabled by Optimal Control on Floquet-Engineered Systems

Superconducting cavities with high quality factors, coupled to nonlinear ancilla, provide a promising platform for quantum information storage and manipulation. However, the commonly used selective number-dependent arbitrary phase (SNAP) gate faces significant challenges in ultra-high-coherence cavities, where weak dispersive shifts result in prolonged gate times. Here, we propose a protocol to achieve high-fidelity SNAP gates that are orders of magnitude faster than the standard implementation, breaking the speed limit set by the bare dispersive shift. This enhancement is achieved by dynamically amplifying dispersive coupling via sideband interactions, followed by quantum optimal control on Floquet-engineered systems. Additionally, we present a unified perturbation theory that explains both the gate acceleration and associated benign drive-induced decoherence, corroborated by Floquet\textendash Markov simulations. These results pave the way for the experimental realization of high-fidelity control of weakly coupled, high-coherence cavities, and expanding the scope of optimal control techniques in Floquet quantum systems.

You, Xinyuan [Fermilab]↗

The Integrated Virtual Blast Furnace: Enabling Physics-Based Operational Guidance

As part of a DOE-supported research effort, Purdue University Northwest researchers are collaborating with Oak Ridge National Laboratory and United States Steel Corporation to develop a tool to provide blast furnace operators and engineers with process performance insight comparable to high-fidelity computational fluid dynamics modeling, accelerated to provide “what-if” scenarios at near-real-time speed. This is accomplished by pre-simulating a baseline case and a range of potential operating scenarios to establish how the furnace responds to changing inputs, then training a neural network-based Reduced Order Model to accelerate the speed at which predictions of key parameters can be generated.

Okosun, Tyamo↗

Two-phase turbine engines

A description is given of a two-phase turbine which utilizes a uniform mixture of gas and liquid accelerated in nozzles of the types reported by Elliott and Weinberg (1968). The mixture acts directly on an axial flow or tangential impulse turbine or is separated into gas and liquid streams which operate separately on a gas turbine and a hydraulic turbine. The basic two-phase cycles are examined, taking into account working fluids, aspects of nozzle expansion, details of turbine cycle operation, and the effect of mixture ratio variation. Attention is also given to two-phase nozzle efficiency, two-phase turbine operating characteristics and efficiencies, separator turbines, and impulse turbine experiments.

Elliott, D. G.↗

Distributed Finite Element Analysis Using a Transputer Network

The principal objective of this research effort was to demonstrate the extraordinarily cost effective acceleration of finite element structural analysis problems using a transputer-based parallel processing network. This objective was accomplished in the form of a commercially viable parallel processing workstation. The workstation is a desktop size, low-maintenance computing unit capable of supercomputer performance yet costs two orders of magnitude less. To achieve the principal research objective, a transputer based structural analysis workstation termed XPFEM was implemented with linear static structural analysis capabilities resembling commercially available NASTRAN. Finite element model files, generated using the on-line preprocessing module or external preprocessing packages, are downloaded to a network of 32 transputers for accelerated solution. The system currently executes at about one third Cray X-MP24 speed but additional acceleration appears likely. For the NASA selected demonstration problem of a Space Shuttle main engine turbine blade model with about 1500 nodes and 4500 independent degrees of freedom, the Cray X-MP24 required 23.9 seconds to obtain a solution while the transputer network, operated from an IBM PC-AT compatible host computer, required 71.7 seconds. Consequently, the $80,000 transputer network demonstrated a cost-performance ratio about 60 times better than the $15,000,000 Cray X-MP24 system.

Watson, James↗

Predicted Performance of a Thrust-Enhanced SR-71 Aircraft with an External Payload

NASA Dryden Flight Research Center has completed a preliminary performance analysis of the SR-71 aircraft for use as a launch platform for high-speed research vehicles and for carrying captive experimental packages to high altitude and Mach number conditions. Externally mounted research platforms can significantly increase drag, limiting test time and, in extreme cases, prohibiting penetration through the high-drag, transonic flight regime. To provide supplemental SR-71 acceleration, methods have been developed that could increase the thrust of the J58 turbojet engines. These methods include temperature and speed increases and augmentor nitrous oxide injection. The thrust-enhanced engines would allow the SR-71 aircraft to carry higher drag research platforms than it could without enhancement. This paper presents predicted SR-71 performance with and without enhanced engines. A modified climb-dive technique is shown to reduce fuel consumption when flying through the transonic flight regime with a large external payload. Estimates are included of the maximum platform drag profiles with which the aircraft could still complete a high-speed research mission. In this case, enhancement was found to increase the SR-71 payload drag capability by 25 percent. The thrust enhancement techniques and performance prediction methodology are described.

Conners, Timothy R.↗

Gust Alleviation Using Direct Gust Measurement

The increasing competition in the market of civil aircraft leads to operating efficiency and passenger comfort being very important sales arguments. Continuous developments in jet propulsion technology helped to reduce energy consumption, as well as noise and vibrations due to the engines. The main problem with respect to ride comfort is, however, the transmittance of accelerations and jerkiness imposed by atmospheric turbulence from the wings to the fuselage. This 'gust' is also a design constraint: Light airplane structures help to save, energy, but are more critical to resist the loads imposed by turbulence. For both reasons, efficient gust alleviation is necessary to improve the performance of modern aircraft. Gust can be seen as a change in the angle of attack or as an additional varying vertical component of the headwind. The effect of gust can be very strong, since the same aerodynamic forces that keep the airplane flying are involved. Event though the frequency range of those changes is quite low, it is impossible for the pilot to alleviate gust manually. Besides, most of the time during the flight, the, autopilot maintains course and the attitude of flight. Certainly, most autopilots should be capable of damping the roughest parts of turbulence, but they are unable to provide satisfactory results in that field. A promising extension should be the application of subsidiary, control, where the inner (faster) control loop alleviates turbulence and the outer (slower) loop controls the attitude of flight. Besides the mentioned ride comfort, another reason for gust alleviation with respect to the fuselage is the sensibility of electrical devices to vibration and high values of acceleration. Many modern airplane designs--especially inherently instable military aircraft--are highly dependent on avionics. The lifetime and the reliability of these systems is thus essential.

Hoppe, Sven Marco↗