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At least 199 records · Page 11

Long-Term Creep Behavior of a CoCrFeNi Medium-Entropy Alloy

We report that current research shows that high-entropy alloys (HEAs) can offer superior oxidation resistance compared to more traditional austenitic stainless steels with equivalent tensile mechanical performance. While many reports have been published on creep of CoCrFeNiMn, few focus on the CoCrFeNi family of low to medium entropy alloys. In this manuscript, uniaxial tensile creep test results for more than 46,000 accumulated hours are presented on the equiatomic CoCrFeNi alloy. The alloy was manufactured at NETL using a vacuum induction melt solidification approach with a computationally designed homogenization cycle. After completing the homogenization cycle, the ingot was first hot forged and then hot rolled into 10 mm thick plate, a product form that is relevant to many industries. Creep tests were performed in the temperature range of 600-650 °C using applied stresses from 120 to 189 MPa. This study builds upon previous results on the CoCrFeNiMn family of high-entropy alloys and offers a modicum of clarification about performance compared to small button melts by using ASTM standard test procedures and mechanical test specimens. The apparent creep activation energy and creep stress exponent were similar to those for CoCrFe medium-entropy and CoCrFeNiMn high-entropy alloys. The post-test creep microstructure showed some Cr segregation, which has also been noted for other CoCrFe alloys. The CoCrFeNi alloy also presents a double minimum or two minimum creep rate phenomena.

36 MATERIALS SCIENCE↗

Landmark-Warped Emulators for Models with Misaligned Functional Response

Many computer models output functional data, and in some cases, these functional data have similar, but misaligned, shape characteristics. In this paper, we introduce a general approach for building emulators for computer models that output misaligned functional data when key values in the functional response (landmarks) can be easily identified. This approach has two main parts: modeling the aligned (using the landmarks) functional data, and modeling the functions that map the misaligned data to the aligned space (warping functions). As the warping functions are required to be monotonic, we give special attention to modeling monotonic functional response data. We discuss how our approach can be easily applied for a variety of typical emulators, such as Gaussian processes, Bayesian multivariate adaptive regression splines, and Bayesian additive regression trees, and how sensitivity analysis can be performed. We demonstrate our approach by building emulators for two applications: (1) a high-energy-density physics computer model used to simulate inertial confinement fusion ignition experiments, where model outputs are highly misaligned, and (2) a multiphysics continuum hydrocode used to simulate high-velocity impact experiments, where model outputs are only slightly misaligned. In case (1) traditional methods cannot be applied, while in (2) they can be applied, but the proposed method performs significantly better.

97 MATHEMATICS AND COMPUTING↗

A Low Loss, Fast Ramp HTS Solenoid Prototype for Compact Spherical Tokamaks

To explore AC loss characteristics of commercial Bi-2212 conductors made in the USA, a small ohmic heating (OH) prototype coil is being developed for compact tokamaks using high performance Bi-2212 wires newly manufactured by Bruker EST. Here, the goal is to build and test Bi-2212 prototype coils for fast ramp central solenoid (CS) operation of spherical tokamaks (ST). For a ST pilot plant, one of the key challenges is the tight space available for CS in a center column where in-board legs of the toroidal field (TF) and OH coils are assembled into a cryostat with a few millimeters clearance. A high current density Rutherford cable consisting of 17 legacy Bi-2212 wires, a contribution of the US Magnet Development Program (MDP), was fabricated at the Lawrence Berkeley National Laboratory (LBNL) for the development of fast ramp CS magnets in the ST Advanced Reactor (STAR) designed by PPPL. Characterization of the new and legacy HTS wires is presented, along with the coil design wound directly with new wire, and a Rutherford cable-wound solenoid using the legacy wire. A comparison of AC losses is made based on expected performance for a fast ramp ST operation. The HTS cable and cabled coil fabrication issues such as the heat treatment, coil mandrel design, assembly and 2212 quench characteristics are discussed, along with a test plan for CS design validation.

Zhai, Yuhu [Princeton Plasma Physics Laboratory (P↗

Quantifying Thermal Performance of the Building Envelope - Beyond Common Practice

Performance metrics serve as useful tools and indicators for many applications. For the building industry, various metrics exist; typically, these metrics do not assess the whole building performance. Instead, these represent separate components or heat transfer mechanisms of a building like R-value, U-factor/value, and airtightness. The mechanisms defined under these metrics all contribute significantly to the overall thermal performance of a building but will rarely act independently. There are metrics that account for the overall energy performance of a building, such as Energy Use Intensity (EUI). However, these metrics tend to be highly influenced by how the building is operated and used. There are also metrics which provide assessment on a relative basis. These indices are based upon comparison to a baseline, which complicates meaningful metric-based energy analyses. This paper presents a performance metric developed to account for various thermal properties and behaviors of a building. The metric accounts for all the relevant mechanisms that influence heat losses and gains in buildings and is thus directly related to the energy performance. In addition, the metric is designed to comprise air infiltration and allows users to account for workmanship quality, and imperfections of the building thermal resistance due to penetrations and other installations. This paper will describe how the metric can be applied for various building types and in different climates.

Pallin, Simon B.↗

Collaboration for Advanced Modeling of Particle Accelerators

The pverarching purpose is to accelerate and expand the scope of discoveries from high energy physics (HEP) particle accelerators by enabling the design of accelerators that are significantly more compact and cheaper to build and run. This will be realized through (i) developing high-performance computing (HPC) accelerator and beam modeling capabilities to design the full range of systems required (ii) developing community simulation ecosystems that seamlessly integrate accelerator elements to facilitate the design and control of next-generation accelerators.

43 PARTICLE ACCELERATORS↗

Deactivation of Building 9206 - A Manhattan Project Era Facility

Building 9206 at the Y-12 National Security Complex was constructed in 1944 for the Manhattan Project as a predecessor to the much larger Building 9212. The purpose of Building 9206 was to perform chemical recycle, metal production, and recover of highly enriched uranium, as well as process product from the electromagnetic separation process.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Monitoring of Unvented Roofs with Fibrous Insulation, Diffusion Vents, and Interior Vapor Control in a Cold Climate

Unvented roof assemblies have been accepted in North American building codes since 2007; code-compliant construction calls for a minimum thickness of “air-impermeable insulation” (based on climate zone) to avoid cold-weather condensation and moisture risks. This is typically implemented with polyurethane spray foam insulation; however, negatives of this material include high first cost and possible adverse environmental impacts. Implementing unvented roofs in a moisture-safe manner with air-permeable fibrous fill insulations (e.g., fiberglass or cellulose) could potentially reduce the first cost of unvented roof designs, allowing for more widespread use. Building unvented roofs in a cost-effective, airtight, and moisture-safe manner opens up options for high-performance house designers and builders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Performance analysis of novel thermal storage integrated heat pump system in a residential building at the hot climate for demand flexibility

A novel thermal energy storage integrated heat pump system was proposed to reshape the electricity load profile of residential buildings while maintaining thermal comfort. High-fidelity computer simulations are needed for evaluating the feasibility of the proposed system. This study investigates the annual performance of the proposed system through Modelica-based system simulations. A rule-based control strategy was developed to shift the electric demand of a typical single-family house in Atlanta, GA from peak to off-peak hours to utilize the Time-of-Use electricity rate to lower the energy costs for conditioning the building. For comparison, a conventional air-source heat pump system serving the same building was also developed. Simulation results indicate that the proposed system is capable of shifting around 90% of the building's electricity consumption for meeting the thermal demand from peak to off-peak hours on a daily basis. In addition, the annual power consumption and operating cost for running the HVAC system can be reduced by 6% and 34%, respectively, compared with the conventional air-source heat pump.

Shi, Liang↗

If We Build Them, They Will Run: Automated HPC Apps Deployment and Profiling with eBPF in Cloud

The high performance computing (HPC) community is in a period of transition. The rise of AI/ML coupled with a changing landscape of resources deems portability a new metric of performance, and methods to move between on-premises and cloud environments and assess compatibility are paramount. Here we design and test a strategy for bridging the gap between traditional HPC and Kubernetes environments – first containerizing applications, providing automated orchestration to run studies, and packaging the setup with automated means to assess performance using low overhead eXtended Berkeley Packet Filter (eBPF) programs. We first assess different designs for eBPF collection, demonstrating a tradeoff between number of programs deployed on a node and overhead added. We develop 5 low overhead eBPF programs that combine with streaming ML models to assess CPU, futex, TCP, shared memory, and file access across four different builds of an HPC application for CPU and GPU. We use eBPF data to generate insights into the possible underlying etiology of scaling issues. We then assess compatibility of a well-known benchmark, HPCG, across matrices of micro-architectures and optimization levels (217 containers across 24 instance types and over 7500 runs). We provide to the community 30 applications to deploy in our automated setup and perform a scaling study from 4 to a maximum of 256 nodes for both CPU and GPU applications. Finally, we use our gained knowledge about performance to generate compatibility artifacts that are used by a newly developed Kubernetes controller to intelligently select instance type based on optimizing a figure of merit. Along with insights to scaling in this environment with a collection of applications and templates to work from, we provide an overall strategy for approaching HPC application deployment and image selection based on compatibility in cloud.

Computer science↗

The Young Supernova Experiment Data Release 1 (YSE DR1): Light Curves and Photometric Classification of 1975 Supernovae

We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multicolor PanSTARRS1 griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host–galaxy associations, redshifts, spectroscopic and/or photometric classifications, and additional data products from 2019 November 24 to 2021 December 20. YSE DR1 spans discoveries and observations from young and fast-rising supernovae (SNe) to transients that persist for over a year, with a redshift distribution reaching z ≈ 0.5. We present relative SN rates from YSE's magnitude- and volume-limited surveys, which are consistent with previously published values within estimated uncertainties for untargeted surveys. We combine YSE and ZTF data, and create multisurvey SN simulations to train the ParSNIP and SuperRAENN photometric classification algorithms; when validating our ParSNIP classifier on 472 spectroscopically classified YSE DR1 SNe, we achieve 82% accuracy across three SN classes (SNe Ia, II, Ib/Ic) and 90% accuracy across two SN classes (SNe Ia, core-collapse SNe). Our classifier performs particularly well on SNe Ia, with high (>90%) individual completeness and purity, which will help build an anchor photometric SNe Ia sample for cosmology. We then use our photometric classifier to characterize our photometric sample of 1483 SNe, labeling 1048 (~71%) SNe Ia, 339 (~23%) SNe II, and 96 (~6%) SNe Ib/Ic. YSE DR1 provides a training ground for building discovery, anomaly detection, and classification algorithms, performing cosmological analyses, understanding the nature of red and rare transients, exploring tidal disruption events and nuclear variability, and preparing for the forthcoming Vera C. Rubin Observatory Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗

Providing Geospatial Intelligence through a Scalable Imagery Pipeline

This chapter describes ORNL’s (Oak Ridge National Laboratory’s) contributions to imagery preprocessing for geospatial intelligence research and development (R&D) in four sections. First, we discuss challenges involved in building an effective imagery preprocessing workflow and the world-class high-performance computing (HPC) resources at ORNL available to process petabytes of imagery data. Second, we highlight how we developed imagery preprocessing tools over three decades while paving the way for our current cutting-edge machine learning and computer vision algorithms that are impacting humanitarian and disaster response efforts. Third, we discuss how PIPE modules work together to turn raw images into analysis-ready datasets. Fourth, we look toward the future and discuss planned advancements to PIPE and computing trends that will affect geospatial intelligence R&D.

Reith, Andrew↗

Conceptual Design of High Field Central Solenoid for Fusion Nuclear Science Facility

Fusion Nuclear Science Facility (FNSF) is a critical fusion nuclear step in the US beyond ITER before proceeding to a larger and electricity producing fusion power plant. Although FNSF is a steady state machine to be operated at high duty cycle, a high field and high current density central solenoid magnet is needed for plasma startups. Due to space constraints in the FNSF in-board radial build, the magnetic field and coil current density required exceed conventional low temperature superconductor (LTS) performance limits and the design can only be achieved by high temperature superconductors (HTS). The design for the central solenoid, also called the ohmic heating (OH) magnet for FNSF shall meet the 100 Weber double flux swing requirement for plasma startups. Finally, the stresses at such a high field and high current density coil may require a bucked and wedged TF-OH design to accommodate space for coil winding support structures in in-board system radial build for high field FNSF operations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Bridging the gap between experiments and simulations using machine learning

The physics of inertial confinement fusion is rich and complex. Simulation codes that are used to design experiments are computationally expensive and lack the predictive capability required for extensive parameter exploration in search of a high-performing design for laser direct drive. In this work we use deep learning to build a fast emulator of experiments. To facilitate the development of the deep-learning model, an autoencoder is used to reduce the dimensionality of the input space. Two deep learning models are developed. One model is trained on a vast array of simulation data and is subsequently calibrated to expensive and limited experimental data using a technique known as “transfer learning.” The other model is trained on a statistical model and is subsequently calibrated using experimental data. A comparative study of the two predictive models is carried out. The models potentially reproduce key experimental observables with high accuracy and unprecedented inference times relative to those achieved with simulation codes. These models facilitate rapid exploration of a high dimensional input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Evaluating dynamic thermal performance of building envelope components using small-scale calibrated hot box tests

The hot box test method has been applied to evaluate both the steady-state (U-value) and dynamic thermal properties of building envelopes. However, the high construction cost of full-scale hot box apparatus and the testing time required (usually several days) may prevent its wider adoption. To overcome the limitations of full-scale hot box tests, here we propose a novel method to evaluate the dynamic thermal performance of building envelope components using a small-scale calibrated hot box and scaled-down specimen. In this paper, the scaling relationships of thermal properties evaluated using a full-size specimen and a scaled-down specimen are established based on the Laplace transform of the heat transfer equations. In addition, dynamic thermal properties obtained from scaled-down experimental tests are compared to the values calculated by the EN ISO13768 (ISO) method. A small-scale hot box with a 355 mm × 355 mm metering area was constructed and calibrated to validate the correlations. Three scaled-down concrete sandwich wall panels were then tested and the scaling relationship was cross-validated using the experimental results, finite difference (FD) simulations, and the ISO method. The results indicate that the dynamic thermal properties obtained from a scaled-down hot box test can be correlated to its full-size counterpart when certain conditions are met. The scaled-down hot box test is demonstrated to be an effective yet economical alternative to a full-scale test with significantly reduced experimentation cost and turn-around time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integration of scanning probe microscope with high-performance computing: Fixed-policy and reward-driven workflows implementation

The rapid development of computation power and machine learning algorithms has paved the way for automating scientific discovery with a scanning probe microscope (SPM). The key elements toward operationalization of the automated SPM are the interface to enable SPM control from Python codes, availability of high computing power, and development of workflows for scientific discovery. Here, we build a Python interface library that enables controlling an SPM from either a local computer or a remote high-performance computer, which satisfies the high computation power need of machine learning algorithms in autonomous workflows. We further introduce a general platform to abstract the operations of SPM in scientific discovery into fixed-policy or reward-driven workflows. Furthermore, our work provides a full infrastructure to build automated SPM workflows for both routine operations and autonomous scientific discovery with machine learning.

47 OTHER INSTRUMENTATION↗

Core performance predictions in projected SPARC first-campaign plasmas with nonlinear CGYRO

This work characterizes the core transport physics of SPARC early-campaign plasmas using the PORTALS-CGYRO framework. Empirical modeling of SPARC plasmas with L-mode confinement indicates an ample window of breakeven (Q > 1) without the need of H-mode operation. Extensive modeling of multi-channel (electron energy, ion energy, and electron particle) flux-matched conditions with the nonlinear CGYRO code for turbulent transport coupled to the macroscopic plasma evolution using PORTALS reveals that the maximum fusion performance to be attained will be highly dependent on the near-edge pressure. Stiff core transport conditions are found, particularly when fusion gain approaches unity, and predicted density peaking is found to be in line with empirical databases of particle source-free H-modes. Impurity optimization is identified as a potential avenue to increase fusion performance while enabling core-edge integration. Extensive validation of the quasilinear TGLF model builds confidence in reduced-model predictions. The implications of projecting L-mode performance to high-performance and burning-plasma devices is discussed, together with the importance of predicting edge conditions.

Rodriguez-Fernandez, P. (ORCID:0000000273611131)↗

Multiscale characterization of phase change materials for building thermal energy storage applications

Phase change materials (PCMs) store and release large amounts of thermal energy because of their high latent energy storage capacity. However, long-term cyclic stability, supercooling and performance-scalability are some of the major challenges for their use in building thermal energy storage (TES) applications. Here, in this study, we present a comprehensive multiscale characterization of two commercially available organic PCMs, Puretemp 18 and Puretemp 23. At the microscale, differential scanning calorimetry (DSC) was used to characterize phase change temperature, specific heat, and latent heat. At the mesoscale, a heat flow meter apparatus (HFMA), following the ASTM C1784 standard, was employed to measure the phase change temperature, specific heat, and latent heat properties. A comparative analysis of latent heat as a function of temperature was conducted by integrating the DSC and HFMA results. At the macroscale, the thermal performance and cyclic stability of the TES system was evaluated using Puretemp 23. The TES system consisted of a finned tube heat exchanger with a storage volume of 0.0189 m 3 (5 gal), which represents a compact, real-world TES solution suitable for building energy storage. The results showed consistent thermal stability of the PCM over 200 cycles, and the supercooling temperature remained within 0.2 °C, which was not detected in smaller-scale characterization methods. Additionally, the macroscale testing methodology of the PCM revealed that the TES is able to charge and discharge stored latent energy within 2 h under a temperature differential of 16.67 °C measured between the inlet water temperature and the phase transition temperature of the PCM. The proposed multiscale PCM characterization method provides a systematic basis for comparing important thermal storage properties while also investigating the scalability, reliability and integration challenges in large scale TES applications.

Latent heat↗

Lessons learned from the development and implementation of a workforce training curriculum for advanced controls for high performance HVAC systems

Over the past decade, academic research on advanced controls has slowly transitioned into new software platforms, giving rise to various companies developing and deploying these innovative products, including solutions for light commercial HVAC systems. However, the current workforce remains widely unprepared to install, maintain and operate these systems, particularly complex software-based control platforms, as most workforce training programs still focus on traditional building automation for large commercial buildings. This paper presents the development and piloting of curriculum for three key types of professionals: ● Technicians (trade-level): installing and maintaining modern high-performance HVAC systems and controls ● Programmers (undergrad-level): developing and implementing advanced controls ● Engineers and energy professionals (undergrad/grad-level): managing and evaluating system performance We share details of the material developed including training videos, open-source software, instruction manuals. We also present the results of a pilot implementation of the training materials with real students.

Casillas, Armando↗