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At least 973 records · Page 54

A portable parton-level event generator for the high-luminosity LHC

The rapid deployment of computing hardware different from the traditional CPU+RAM model in data centers around the world mandates a change in the design of event generators for the Large Hadron Collider, in order to provide economically and ecologically sustainable simulations for the high-luminosity era of the LHC. Parton-level event generation is one of the most computationally demanding parts of the simulation and is therefore a prime target for improvements. We present a production-ready leading-order parton-level event generation framework capable of utilizing most modern hardware and discuss its performance in the standard candle processes of vector boson and top-quark pair production with up to five additional jets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Savannah River Site Environmental Report for 2011

The Savannah River Site Environmental Report for 2011 (SRNS-STI-2012-00200) is an overview of effluent monitoring and environmental surveillance activities conducted on and in the vicinity of SRS from January 1 through December 31, 2011 - including the Site’s performance against applicable standards and requirements. Details are provided on major programs such as the Environmental Management System (EMS) and permit compliance. Information for the 2011 report was compiled and prepared by the Environmental Compliance and Area Completion Projects (EC&ACP) Department of Savannah River Nuclear Solutions LLC (SRNS), the Site’s Management and Operations (M&O) contractor. The “Environmental Monitoring Program Management Plan” (SRS EM Plan, 2010) documents 1) the rationale and objectives for the monitoring program, 2) the frequency of monitoring and analysis, 3) the various sampling locations, and 4) the specific analytical and sampling protocols used. The “Environmental Monitoring Quality Assurance Project Plan” (SRS EM QA Plan, 2010) describes the associated quality assurance requirements.

54 ENVIRONMENTAL SCIENCES↗

Collaboration Leads to State-of-the-Art Energy Auditing Tool: Project Highlights (Fact Sheet)

This fact sheet describes the tablet-based simuwatt Audit tool, which uses NREL's advanced energy modeling framework and building energy audit processes, collaboration tools, in-app media, and private company concept3D's geometric capture software combined with real-time connections to large sets of standardized data to perform building energy audits faster than traditional methods. By integrating the NREL Building Component Library, utility rates, weather information, and energy conservation measures, the tool provides investment-grade audits that cost 75% less than traditional audits and stores the data in a consistent and reusable format.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Savannah River Site Environmental report for 2012

This report is an overview of effluent monitoring and environmental surveillance activities conducted on and in the vicinity of SRS from January 1 through December 31, 2012 - including the Site's performance against applicable standards and requirements. Details are provided on major programs such as the Environmental Management System (EMS) and permit compliance.

54 ENVIRONMENTAL SCIENCES↗

High-dose neutron detector development

The development of advanced sustainable nuclear fuel cycles relying on used nuclear fuel is one of the key programs pursued by the DOE Office of Nuclear Energy to minimize waste generation, limit proliferation risk and maximize energy production using nuclear energy. Safeguarding of advanced nuclear fuel cycles is essential to ensure the safety and security of the nuclear material. Current non-destructive assay (NDA) systems typically employ fission chambers or 3He-based tubes for the measurement of used fuel. Fission chambers are capable of withstanding the high gamma-ray backgrounds; however, they provide very low detection efficiency on the order of 0.01%. To benefit from the additional information provided by correlated neutron counting [1] higher detection efficiencies are required. 3He-based designs allow for higher detection efficiencies; however, at the expense of slow signal rise time characteristics and higher sensitivity to the gamma-ray backgrounds. It is therefore desirable to evaluate and develop technologies with potential to exceed performance parameters of standard fission chamber-based or 3He-based detection systems currently used in the NDA instrumentation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Magnetostrictive Cold Spray Sensor Feasibility Assessment

Ultrasound sensors and inspection systems are frequently used to generate acoustic waves in metal structures capable of detecting and characterizing cracks, pits, erosion, inclusions, weld anomalies, and other material and structural features. One significant problem with piezoelectric transducers is the difficulty to achieve good coupling between the transducer and the surface being examined. This is particularly true in harsh conditions with high temperatures, cyclical hot and cold temperatures, highly radioactive fields found near nuclear reactors or spent nuclear fuel, caustic or corrosive fluids, and other extreme environmental conditions, as well as in long-term monitoring applications where repair or replacement of the sensor is difficult or expensive. Typically, coupling between the surface and the transducer is achieved with water, gel, grease, viscous shear coupling material, or pressure, which might not be possible or appropriate for long-term applications in which the impedance -matching materials wear away, evaporate, or simply stop functioning due to changes in surface conditions. Fluid couplings can evaporate or drain away from the transducer-substrate interface; glue- based couplings may foul or fail and are notoriously unreliable at high temperatures and in radioactive environments. This work explores the behavior of a magnetostrictive cold-spray patch that is metallurgically bonded to a stainless steel inspection target surface, and compares it to the performance of a standard adhesively-bonded ferrous-cobalt magnetostrictive strip solution. Cold-spray is a coating process where 10 –100 micron diameter powdered metal is accelerated to Mach 2 to Mach 3 (2–3 × speed of sound) and impacted on the surface to be coated. Each powder particle forms a kinetic bond with the substrate or other coating particles to produce a metallurgically bonded layer. If the powder is nickel or cobalt with high magnetostrictive coefficients, this surface can serve as the base of a magnetostrictive sensor suitable for crack or pitting-damage inspection and monitoring that is not subject to temporal or environmental degradation.

47 OTHER INSTRUMENTATION↗

Diagnostics for Stationary Planetary-scale Waves

The largest waves in Earth’s atmosphere are nearly stationary and thus appear in monthly means of pressure and temperature. But they evolve slowly with time, forming a link between weather and climate. For example, droughts in California are associated with persistent high pressure off the west coast of North America that directs storms poleward; the high pressure areas, in turn, are often linked to climate shifts in the western tropical Pacific (e.g. Trenberth 1988, Molteni et al. 2015, Scaife et al. 2017). With numerical models of weather and climate, a necessary condition for believing predictions of the future is that the models accurately simulate a background unperturbed climatology. Therefore the PCMDI is establishing a standard set of performance metrics for climate models that compares observations with simulations of key space-time fields (Gleckler et al. 2016). This technical report proposes an additional metric involving quasi-stationary, planetary-scale waves in atmospheric geopotential Φ.

54 ENVIRONMENTAL SCIENCES↗

ChIMES: A Machine-Learned Interatomic Model Targeting Improved Description of Condensed Phase Chemistry in Energetic Materials

In this report we detail completion of a Physics and Engineering Model Level Two Milestone targeting improved reactive interatomic potentials (IAPs) for energetic materials (EM) through machine learning. The specific goals of this milestone were to develop, validate, and document a new reactive molecular dynamics method for EM, based on machine learning by (1) generating databases of first-principles-derived forces, stresses, and energies for HN3 and 3,4-bis(3-nitrofurazan- 4-yl)furoxan (DNTF) (2) generate atomistic force fields from these databases via ML, and (3) benchmark model performance against first principles calculations. These goals were achieved by (1) further developing a machine learned reactive IAP and generation approach (i.e. the Chebyshev Interaction Model for Efficient Simulation or “ChIMES”), for which resulting IAPs can approach the predictive power of quantum-mechanical approaches at a fraction of the computational expense, and (2) applying the ChIMES framework to develop models for HN3 and DNTF. We find that for simple energetic materials like HN3, high accuracy ChIMES models can be obtained through application of a fitting approach that does not use active machine learning. We demonstrate the suitability of ChIMES models for simulations involving EM by using the HN3 model in multiscale shock technique simulations to predict the HN3 Chapman-Jouguet detonation state and investigate chemical evolution out to 1 ns following shock compression. This model is then used in larger direct shock (DS) simulations for a preliminary investigation of how bubbles (i.e. voids) influence material response under shock compression. We find that more complex EM (i.e. DNTF) necessitate a more sophisticated fitting approach, and develop a new active learning method and python tool to meet this challenge. We demonstrate that this fitting approach yields ChIMES models that out-perform commonly used standard reactive IAPs as well as semi-empirical quantum methods, and discuss the systematic improvability of these actively learned ChIMES models. We also describe challenges related to model development for EM such as DNTF, for which few experimental or previous simulation data are available (e.g. which could otherwise inform generation of training data). To overcome this issue, we establish a semi-empirical quantum ChIMES capability which can be used to efficiently map out relevant thermodynamic and configurational space, and generate ChIMES-IAP training data in a multiscale manner. We also show that these semi-empirical quantum ChIMES models can be used to generate predictions for the shock Hugoniot (the Hugoniot is the locus of thermodynamic states found in a shocked material) equation of state, investigate related thermochemistry, and explore carbon condensation following shock compression. This work represents a substantial advance in our atomistic modeling capability for EM that will provide much needed information on the chemistry of detonation for continued development of continuum models based on the Cheetah thermochemical code.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Small Punch Testing of Molybdenum-99 Targets

Northstar Medical Radioisotopes is developing an accelerator-based method to produce 99 Mo, which is a parent isotope of the commonly used 99m Tc medical isotope. The Mo targets being designed for the accelerator will be produced from enriched 100 Mo, also known as aMo . Pressed and sintered powder feedstock is used to fabricate aMo targets, producing 29 mm disk-shaped targets. The targets are subjected to 1–6 days in line of an electron beam with subsequent dissolution of the disk to retain the 99 Mo, which decays to 99m Tc at radio-pharmacies. The press and sinter method is advantageous because the inherent porosity produced by this method enables increased surface area and therefore increased flow of dissolution media, decreasing the dissolution time and reducing the need for a highly acidic media. Although porosity aids in dissolution, it reduces the mechanical strength and ductility. Targets require good mechanical integrity when subjected to the conditions in the accelerator. Therefore, Northstar is seeking methods to rapidly test disk samples after fabrication to assure mechanical performance metrics are achieved. This report details the design and testing of a small punch test (SPT) that accommodates the 29 mm disk. Initial data were used to relate the SPT data to tensile properties, such as the yield strength (YS), ultimate tensile strength (UTS), and total elongation to failure. Although the SPT has been established as a somewhat reliable method for testing metallic materials, few studies have applied the SPT to refractory materials such as Mo. Based on tensile testing performed at Oak Ridge National Laboratory on different Mo samples, correlation between the Mo tensile and SPT properties could be performed, establishing a standard calibration that could be applied to other Mo samples. To test the efficacy of the SPT with Mo, multiple different disk batches were fabricated under different conditions (e.g., pressure, lubricant) with commercially available pure Mo powder. Generally, only a UTS could be well defined because the press and sinter disks failed under brittle fracture, making it difficult to determine the YS and elongation. Compared with disks fabricated with aMo powder, the aMo samples underperformed their pure nat Mo counterparts. This report summarizes the current status of the SPT, but further evaluation is needed before it can be applied as a reliable quality assurance tool.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

MicroED for rapid and comprehensive characterization of the unknown small molecule composition of crude plant and soil extracts

This project implemented at PNNL a method introduced recently for de novo structure elucidation of small organic molecules: Micro-Electron Diffraction (henceforth microED). Micro-ED is an alternative to X-ray diffraction (XRD) or Nuclear Magnetic Resonance (NMR) for atomic-resolution structure elucidation of small organic or biological molecules, and it can succeed in solving structures when these well-established methods fail. In particular, microED offers the possibility of determining structures from far smaller quantities of material than would be required for NMR or even XRD, or from substances that fail to form crystals suitable (i.e., large enough) for X-ray crystallography, because microED requires only microcrystalline samples: in principle, a single crystal with ca. 100 nm dimensions would be suitable. MicroED is performed typically with standard electron microscopy (EM) instrumentation. The substantial potential of microED has drawn significant attention and examples of its use to solve difficult structure elucidation problems where X-ray or NMR methods failed has been described recently.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Autonomous Fueling System for Heavy-Duty Fuel Cell Electric Trucks

The motivation for this project stemmed from the challenges associated with rapidly refueling heavy-duty hydrogen fuel cell electric trucks (FCETs). Current manual refueling processes for fast refueling involve large, heavy equipment (e.g., hoses three times heavier than standard) and pose ergonomic risks and potential for equipment damage. The goal was to develop and test an autonomous fueling system to improve ergonomics, enhance safety, increase equipment durability through design improvements, and potentially speed up the fueling process. This project aimed to add to the understanding of autonomous systems in the context of heavy-duty hydrogen refueling, evaluating the technical effectiveness of potential concepts. A successfully developed system would benefit the public by facilitating the adoption of zero-emission heavy-duty transport, reducing reliance on manual labor for a physically demanding task, and potentially improving the safety and efficiency of hydrogen refueling infrastructure. The major accomplishment during the project's active period was the completion of the system-level architecture task. This involved establishing a detailed list of system requirements covering interfaces, environmental conditions, regulatory compliance, industry standards, safety, security, performance capabilities, and optional features. Five key use cases for the autonomous system were also identified. However, due to internal restructuring at Nikola, the necessary resources could not be allocated to continue the project. Consequently, Nikola opted to discontinue the project. The award was mutually terminated by Nikola and the DOE.

08 HYDROGEN↗

Evaluating Tools and Technologies for Monitoring Baleen Whales During Offshore Wind Foundation Installation

Impacts to baleen whales are of particular concern in the context of offshore wind development because of their conservation status, the overlap of their habitat with current and planned offshore wind energy facilities, and their expected sensitivity to low-frequency sounds, such as those produced during pile driving. Therefore, this report focuses on monitoring technologies capable of detecting this species group. The scope of this report is to assess the current state of technologies and methods for monitoring baleen whales in low- and no-light conditions in conjunction with offshore wind foundation installation. This work considers the performance of various sensing technologies that can be used to observe the presence of baleen whales near offshore construction activities. The scope of work includes: 1. Technology Performance Metrics – Identify metrics that can be used to assess technology performance. 2. Technology Evaluation – Synthesize the past performance of technologies with respect to the performance metrics based on available literature. 3. Technology Characterization Framework – Describe a potential framework to characterize technology performance with a standardized approach. 4. Technology Research and Development Needs – Identify future needs and opportunities for research, development, and deployment to improve technologies.

17 WIND ENERGY↗

Machine Learning Analysis of Temperature-Strain Relationships for Structural Health Monitoring of Pipes: Self-powered wireless sensor system for health monitoring of liquid-sodium cooled fast reactors

This report presents machine learning (ML) analysis of temperature-strain relationships for structural health monitoring of nuclear reactor stainless steel (SS) pipes with the strain gauge sensor directly printed on the pipe with a 3D conformal aerosol jet printer. We investigate correlations for two sensor pairs installed on the same SS304 pipe: commercial K-type thermocouple with a printed gold strain gauge (TC3-SG3), and commercial K-type thermocouple with commercial Kyowa strain gauge (TC0-SG0). The temperature ranges for the sensor pairs TC0-SG0 and TC3-SG3 are 20.00°C to 266.37°C and 39.95°C to 219.28°C respectively. ML algorithms in this study include Linear Regression (baseline method), Ridge Regression, Lasso Regression, and Gradient Boosting. Performance evaluation metrics include Root Mean Square Error (RMSE), Mean Square Error (MSE), Mean Absolute Error (MAE), R 2 Score, and Explained Variance. Using advanced feature engineering techniques, we extracted 27 temperature-based features and 30 strategic inclusion features. The best performance was obtained with the Gradient Boosting method, which achieves prediction accuracy of R 2 = 0.9999 and RMSE = 7.69 μStrain for TC0-SG0, and R 2 = 0.9998 and RMSE = 18.03 μStrain for TC3-SG3. While the temperature-strain correlations are weaker for the gauge directly printed on the pipe than for the commercial strain gauge, deployment-ready performance exceeding industry standards is achieved for both sensor pairs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Solution-Processed Oxide Thin Films for Perovskite Photovoltaics (Final Report)

The overarching goal of the voucher project is to evaluate the suitability of NexTC materials as functional layers in perovskite photovoltaic technology. There are several different perovskite device configurations that are being pursued for commercialization. Most are superstrate configuration (light enters the device through the glass substrate) and can be subdivided into two categories: PIN and NIP. At minimum, PIN devices have a transparent conductor (typically Indium Tin Dioxide [ITO] or Fluorine-Doped Tin Oxide [FTO]) and hole transport layer (HTL) deposited on glass before the perovskite is deposited. Alternatively, NIP devices have a transparent conductor and electron transport layer (ETL) deposited before the perovskite is deposited. NexTC produces several inks that can be deposited to replace or modify the transparent conductor and/or the ETL or HTL, depending on the device. NLR will produce PIN and NIP perovskite devices on substrates that have been coated by NexTC and compare to NLR-standard devices that perform among the best for research labs across the world. The work will ultimately expose NexTC products to the up-and-coming perovskite PV industry.

14 SOLAR ENERGY↗

Improving unfolding and systematic uncertainty estimation using generative diffusion networks (Final Technical Report)

This final technical report summarizes the key accomplishments on the unfolding using diffusion model project, a DOE award received by PI Pierre-Hugues Beauchemin at Tufts University. This project main goal was to investigate the potential of diffusion models for unfolding experimental High Energy Physics data from detector effects while controlling systematics uncertainties. The project accomplished its goals by completing the following objectives: 1) Performing an object-by-object, event-by-event unfolding of various kinematic distributions reconstructed from detector data in HEP in a way that keeps correlations between unfolded observables while demonstrating competitive performance compared to standard algorithms used in the field; 2) Address the generalization problem by developing an unfolding algorithm capable to correctly infer the underlying distributions of observables and processes never seen before, while controlling the dominant theoretical uncertainties affecting the process, therefore increasing the effectiveness, the precision, and the applicability of the developed algorithm; 3) Understand the theoretical foundations between the developed algorithm so to extend it to applications beyond experimental HEP, for broader benefits to the society. This report provides an overview of the accomplishments related to each of these key objectives.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Cellulose molecular weight of corn stover with cotreatment

Here we present a dataset of cellulose molecular weights from corn stover after a cotreatment process. The corn stover sample was subjected to a combination of mechanical disruption (ball milling) and consolidated bioprocessing (CBP) process using the bacterium C. thermocellum at 60 grams/L solids loadings. Cellulose was isolated from control, no cotreatment control, and cotreatment corn stover. Cellulose was then derivatized using anhydrous pyridine and phenyl isocyanate over 48 h at 70 ºC. The reaction was quenched by anhydrous methanol. Methanol and water mixture (7:3, v/v) was added dropwise to promote precipitation of the cellulose derivative. The solids were collected by filtration and thoroughly washed with the methanol and water mixture followed by water. The cellulose derivative was dried overnight under vacuum at 40°C. The obtained cellulose tricarbanilates was then dissolved in tetrahydrofuran (THF) at 1.0 mg/mL and the solution was filtered through a 0.45 µm PTFE filter and placed in an auto-sampler vial. The molecular weight of cellulose was measured by Agilent GPC SECurity 1200 system equipped with four Waters Styragel columns (i.e., HR0.5, HR2, HR4, and HR6) and a UV detector (270 nm). THF was used as the mobile phase. Data collection and processing was performed by Polymer Standards Service WinGPC Unity software (Build 6807). The molecular weight was calculated relative to the polystyrene calibration curve. The data on molecular weights provided information about the effects of cotreatment on corn stover cellulose molecular changes.

Cellulose, molecular weights, corn stover, cotreat↗

Globally optimal interferometry with lossy twin Fock probes

Parity or quadratic spin (e.g., J z 2 ) readouts of a Mach–Zehnder (MZ) interferometer probed with a twin Fock (TF) input state allow saturating the optimal sensitivity attainable among all mode-separable states with a fixed total number of particles but only when the interferometer phase θ is near zero. When more general Dicke state probes are used, the parity readout saturates the quantum Fisher information (QFI) at θ = 0, whereas better-than-standard quantum limit performance of the J z 2 readout is restricted to an o ( N ) occupation imbalance. We show that a method of moments readout of two quadratic spin observables J z 2 and J + 2 + J − 2 is globally optimal for Dicke state probes; i.e., the error saturates the QFI for all θ . In the lossy setting, we derive the time-inhomogeneous Markov process describing the effect of particle loss on TF states, showing that the method of moments readout of four at-most-quadratic spin observables is sufficient for globally optimal estimation of θ when two or more particles are lost. The analysis culminates in a numerical calculation of the QFI matrix for distributed MZ interferometry on the four-mode state | N 4 , N 4 , N 4 , N 4 〉 and its lossy counterparts, showing that an advantage for the estimation of any linear function of the local MZ phases θ 1 and θ 2 (compared to independent probing of the MZ phases by two copies of | N 4 , N 4 〉 ) appears when more than one particle is lost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Inpainting Galactic Foreground Intensity and Polarization Maps Using Convolutional Neural Networks

The Deep Convolutional Neural Networks (DCNNs) have been a popular tool for image generation and restoration. In this work, we applied DCNNs to the problem of inpainting non-Gaussian astrophysical signal, in the context of Galactic diffuse emissions at the millimetric and submillimetric regimes, specifically Synchrotron and Thermal Dust emissions. Both signals are affected by contamination at small angular scales due to extragalactic radio sources (the former) and dusty star-forming galaxies (the latter). Furthermore, we compare the performance of the standard diffusive inpainting with that of two novel methodologies relying on DCNNs, namely Generative Adversarial Networks and Deep-Prior. We show that the methods based on the DCNNs are able to reproduce the statistical properties of the ground-truth signal more consistently with a higher confidence level.

79 ASTRONOMY AND ASTROPHYSICS↗