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At least 991 records · Page 55

A comparison of cosmological models using time delay lenses

The use of time-delay gravitational lenses to examine the cosmological expansion introduces a new standard ruler with which to test theoretical models. The sample suitable for this kind of work now includes 12 lens systems, which have thus far been used solely for optimizing the parameters of ΛCDM. In this paper, we broaden the base of support for this new, important cosmic probe by using these observations to carry out a one-on-one comparison between competing models. The currently available sample indicates a likelihood of ∼70%-80% that the R {sub h} = ct universe is the correct cosmology versus ∼20%-30% for the standard model. This possibly interesting result reinforces the need to greatly expand the sample of time-delay lenses, e.g., with the successful implementation of the Dark Energy Survey, the VST ATLAS survey, and the Large Synoptic Survey Telescope. In anticipation of a greatly expanded catalog of time-delay lenses identified with these surveys, we have produced synthetic samples to estimate how large they would have to be in order to rule out either model at a ∼99.7% confidence level. We find that if the real cosmology is ΛCDM, a sample of ∼150 time-delay lenses would be sufficient to rule out R {sub h} = ct at this level of accuracy, while ∼1000 time-delay lenses would be required to rule out ΛCDM if the real universe is instead R {sub h} = ct. This difference in required sample size reflects the greater number of free parameters available to fit the data with ΛCDM.

79 ASTRONOMY AND ASTROPHYSICS↗

Coupling-dependent antiferromagnetic-ferromagnetic ordering in a pinwheel artificial spin ice

Nanopatterned magnetic thin films offer a platform for exploration of tailored magnetic properties such as emergent long-range order. A prominent example is artificial spin ice (ASI), where an arrangement of nanoscale magnetic elements, acting as macrospins, interact via their dipolar fields. In this study, we discuss the transition from antiferromagnetic (AFM) to ferromagnetic (FM) long-range order in a square lattice ASI as the magnetic elements are gradually rotated through 45⁢° to a “pinwheel” configuration. The AFM-FM transition is observed experimentally using synchrotron radiation x-ray spectromicroscopy and occurs for a certain rotation angle of the nanomagnets, dependent on the dipolar coupling strength determined by the separation of the magnets in the lattice. Large-scale magnetic dipole simulations show that the point-dipole approximation fails to capture the correct AFM-FM transition angle. However, excellent agreement with experimental data is obtained using a dumbbell-dipole model, which better reflects the actual dipolar fields of the magnets. This model also explains the coupling dependence of the transition angle, another feature not captured by the point-dipole model. Our findings resolve a discrepancy between measurement and theory in previous work on “pinwheel” ASIs and establish the coupling dependence of the AFM-FM transition. The revised dipole model, with a more accurate representation of the stray field, offers more precise control of magnetic order in artificial spin systems.

Artificial spin ice↗

Radiological Survey of Pajarito Site (Technical Area 18) for the Manhattan Project Historical Park

Environmental Protection Compliance-Environmental Stewardship (EPC-ES) has evaluated radiological process history and all measurement data and found: (1) soil and interior surface sampling meet the data quality objectives contained in MARSSIM (2000) and MARSAME (2009), as reflected in LANL procedures (LANL 2015a, 2015b), (2) that the interiors of the Slotin Building, Pond Cabin and Battleship Bunker were within surface contamination limits for unrestricted access, and (3) the soils around the Slotin Building, Pond Cabin and Battleship Bunker are below Screening Action Levels for both construction work and recreational use (LANL 2016). Therefore, public access inside the Slotin Building and to the outside areas surrounding the Slotin Building, Pond Cabin and Battleship Bunker area are not restricted. This finding is consistent with the requirements of DOE Order 458.1 “Radiation Protection of the Public and the Environment” (DOE 2013) and LANL procedure “Environmental Radiation Protection” (LANL 2018).

54 ENVIRONMENTAL SCIENCES↗

Femtosecond Reflectance Spectroscopy for Energetic Material Diagnostics

Understanding the fundamental mechanisms underpinning shock initiation is critical to predicting energetic material (EM) safety and performance. Currently, the timescales and pathways by which shock-excited lattice modes transfer energy into specific chemical bonds remains an open question. Towards understanding these mechanisms, our group has previously measured the vibrational energy transfer (VET) pathways in several energetic thin films using broadband, femtosecond transient absorption spectroscopy. However, new technologies are needed to move beyond these thin film surrogates and measure broadband VET pathways in realistic EM morphologies. Herein, we describe a new broadband, femtosecond, attenuated total reflectance spectroscopy apparatus. Performance of the system is benchmarked against published data and the first VET results from a pressed EM pellet are presented. This technology enables fundamental studies of VET dynamics across sample configurations and environments (pressure, temperature, etc .) and supports the potential use of VET studies in the non-destructive surveillance of EM components.

42 ENGINEERING↗

Algal Biomass Production via Open Pond Algae Farm Cultivation: 2023 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office (BETO). It allows for the impact of research progress (both directly achieved in-house at the National Renewable Energy Laboratory [NREL] and furnished by partner organizations) to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked toward out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae SOT benchmarking efforts historically focused both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted primarily under NREL research and development projects. This report focuses on front-end algal biomass production, documenting the pertinent algal biomass cultivation parameters that were input to the NREL open pond algae farm model. Through partnerships under DISCOVR, collaborators at ASU furnished details on cultivation performance metrics including biomass productivity and harvest densities for recent growth trials done at the AzCATI site. The resulting biomass productivity was calculated at 16.7 g/m 2 /day (ash-free dry weight [AFDW], annual average) for seasonal cultivation of Picochlorum celeri TG2 and Monoraphidium minutum 26B-AM biomass strains at the ASU site. Picochlorum celeri achieved the best productivity from April to September, with Monoraphidium minutum 26B-AM being used between October and March. Tetraselmis striata LANL1001, usually part of the strain rotation in previous cultivation SOTs, was supplanted by Monoraphidium minutum 26B-AM in this year's outdoor cultivation trials. Finally, building from an industry case study presented in the 2022 SOT report, in the Appendix of this report we provide an update on further improved data furnished by an industry collaborator and resultant impacts on economics reflecting several seasonal scenarios. This case study provides a supplementary datapoint on work being performed elsewhere with a more dedicated focus on improved compositional quality, producing biomass enriched in lipids as may be more optimal for conversion upgrading to fuels and products.

09 BIOMASS FUELS↗

A Spectroscopic Study of Mars-analog Materials with Amorphous Sulfate and Chloride Phases: Implications for Detecting Amorphous Materials on the Martian Surface

The Chemistry and Mineralogy X-ray diffraction (XRD) instrument aboard the Curiosity rover consistently identifies amorphous material at Gale Crater, which is compositionally variable, but often includes elevated sulfur and iron, suggesting that amorphous ferric sulfate (AFS) may be present. Understanding how desiccating ferric sulfate brines affect the spectra of Martian material analogs is necessary for interpreting complex/realistic reaction assemblages. Visible and near-infrared reflectance (VNIR), mid-infrared attenuated total reflectance (MIR, FTIR-ATR), and Raman spectra, along with XRD data are presented for basaltic glass, hematite, gypsum, nontronite, and magnesite, each at three grain sizes (<25, 25–63, and 63–180 μm), mixed with ferric sulfate (+/–NaCl), deliquesced, then rapidly desiccated in 11% relative humidity or via vacuum. All desiccated products are partially or completely XRD amorphous; crystalline phases include starting materials and trace precipitates, leaving the bulk of the ferric sulfate in the amorphous fraction. Due to considerable spectral masking, AFS detectability is highly dependent on spectroscopic technique and minerals present. This has strong implications for remote and in situ observations of Martian samples that include an amorphous component. AFS is only identifiable in VNIR spectra for magnesite, nontronite, and gypsum samples; hematite and basaltic glass samples appear similar to pure materials. Sulfate features dominate Raman spectra for nontronite and basaltic glass samples; the analog material dominates Raman spectra of hematite and gypsum samples. MIR data are least affected by masking, but basaltic glass is almost undetectable in MIR spectra of those mixtures. NaCl produces similar FTIR-ATR and Raman features, regardless of analog material.

58 GEOSCIENCES↗

An ecosystem-scale perspective of the net land methanol flux: synthesis of micrometeorological flux measurements

We present field observations made in June 2011 downwind of Dallas-Fort Worth, TX, and evaluate the role of stabilized Criegee radicals (sCIs) in gaseous sulfuric acid (H2SO4) production. Zero-dimensional model calculations show that sCI from BVOCs composed the majority of the sCIs. The main uncertainty associated with an evaluation of H2SO4 production from the sCI reaction channel is the lack of experimentally determined reaction rates for sCIs formed from isoprene ozonolysis with SO2. In general, the maximum of H2SO4 production from the sCI channel is found in the late afternoon as ozone increases towards the late afternoon. The sCI channel, however, contributes minor H2SO4 production compared with the conventional OH channel. Finally, The production and the loss rates of H2SO4 are compared. The application of the recommended mass accommodation coefficient causes significant overestimation of H2SO4 loss rates compared with H2SO4 production rates. On the other hand, the application of a lower experimental value for the mass accommodation coefficient provides good agreement between the loss and production rates of H2SO4. The results suggest that the recommended coefficient for the H2O surface may not be suitable for this relatively dry environment.

Wohlfahrt, G.↗

KAZRCORGE

For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorge.c1 (ge=general sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity.

54 ENVIRONMENTAL SCIENCES↗

KAZRCORMD

For the Ka ARM Zenith Radar (KAZR) data stream, kazrcormd.c1 (md=moderate sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity.

54 ENVIRONMENTAL SCIENCES↗

KAZRCORHI

For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorhi.c1 (hi=high sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity.

54 ENVIRONMENTAL SCIENCES↗

KAZRCORGE-c0

For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorge.c1 (ge=general sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity. Note that reflectivity in this product is not calibrated.

54 ENVIRONMENTAL SCIENCES↗

KAZRCORHI-c0

For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorhi.c1 (hi=high sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity. Note that reflectivity in this product is not calibrated.

54 ENVIRONMENTAL SCIENCES↗

KAZRCORMD-c0

For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorge.c1 (ge=general sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity. Note that reflectivity in this product is not calibrated.

54 ENVIRONMENTAL SCIENCES↗

Advancements in Wind Integration Study Data Modeling: The Wind Integration National Dataset (WIND) Toolkit; Preprint

Regional wind integration studies in the United States require detailed wind power output data at many locations to perform simulations of how the power system will operate under high-penetration scenarios. The wind data sets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as be time synchronized with available load profiles. The Wind Integration National Dataset (WIND) Toolkit described in this paper fulfills these requirements. A wind resource dataset, wind power production time series, and simulated forecasts from a numerical weather prediction model run on a nationwide 2-km grid at 5-min resolution will be made publicly available for more than 110,000 onshore and offshore wind power production sites.

17 WIND ENERGY↗

Methodology for the Incorporation of Passive Component Aging Modeling into the RAVEN/ RELAP-7 Environment

Passive system, structure and components (SSCs) will degrade over their operation life and this degradation may cause to reduction in the safety margins of a nuclear power plant. In traditional probabilistic risk assessment (PRA) using the event-tree/fault-tree methodology, passive SSC failure rates are generally based on generic plant failure data and the true state of a specific plant is not reflected realistically. To address aging effects of passive SSCs in the traditional PRA methodology [1] does consider physics based models that account for the operating conditions in the plant, however, [1] does not include effects of surveillance/inspection. This paper represents an overall methodology for the incorporation of aging modeling of passive components into the RAVEN/RELAP-7 environment which provides a framework for performing dynamic PRA. Dynamic PRA allows consideration of both epistemic and aleatory uncertainties (including those associated with maintenance activities) in a consistent phenomenological and probabilistic framework and is often needed when there is complex process/hardware/software/firmware/ human interaction [2]. Dynamic PRA has gained attention recently due to difficulties in the traditional PRA modeling of aging effects of passive components using physics based models and also in the modeling of digital instrumentation and control systems. RAVEN (Reactor Analysis and Virtual control Environment) [3] is a software package under development at the Idaho National Laboratory (INL) as an online control logic driver and post-processing tool. It is coupled to the plant transient code RELAP-7 (Reactor Excursion and Leak Analysis Program) also currently under development at INL [3], as well as RELAP 5 [4]. The overall methodology aims to: • Address multiple aging mechanisms involving large number of components in a computational feasible manner where sequencing of events is conditioned on the physical conditions predicted in a simulation environment such as RELAP-7. • Identify the risk-significant passive components, their failure modes and anticipated rates of degradation • Incorporate surveillance and maintenance activities and their effects into the plant state and into component aging progress. • Asses aging affects in a dynamic simulation environment 1. C. L. SMITH, V. N. SHAH, T. KAO, G. APOSTOLAKIS, “Incorporating Ageing Effects into Probabilistic Risk Assessment –A Feasibility Study Utilizing Reliability Physics Models,” NUREG/CR-5632, USNRC, (2001). 2. T. ALDEMIR, “A Survey of Dynamic Methodologies for Probabilistic Safety Assessment of Nuclear Power Plants, Annals of Nuclear Energy, 52, 113-124, (2013). 3. C. RABITI, A. ALFONSI, J. COGLIATI, D. MANDELLI and R. KINOSHITA “Reactor Analysis and Virtual Control Environment (RAVEN) FY12 Report,” INL/EXT-12-27351, (2012). 4. D. ANDERS et.al, "RELAP-7 Level 2 Milestone Report: Demonstration of a Steady State Single Phase PWR Simulation with RELAP-7," INL/EXT-12-25924, (2012).

97 MATHEMATICS AND COMPUTING↗

Quantifying Adoption Rates and Energy Savings Over Time for Advanced Manufacturing Technologies

Energy-efficient manufacturing technologies can reduce energy consumption and lower operating costs for an individual manufacturing facility, but increased process complexity and the resulting risk of disruption means that manufacturers may be reluctant to adopt such technologies. In order to quantify potential energy savings at scales larger than a single facility, it is necessary to account for how quickly and how widely the technology will be adopted by manufacturers. This work develops a methodology for estimating energy-efficient manufacturing technology adoption rates using quantitative, objectively measurable technology characteristics, including energetic, economic and technical criteria. Twelve technology characteristics are considered, and each characteristic is assigned an importance weight that reflects its impact on the overall technology adoption rate. Technology characteristic data and importance weights are used to calculate the adoption score, a number between 0 and 1 that represents how quickly the technology is likely to be adopted. The adoption score is then used to estimate parameters for the Bass diffusion curve, which quantifies the change in the number of new technology adopters in a population over time. Finally, energy savings at the sector level are calculated over time by multiplying the number of new technology adopters at each time step with the technology's facility-level energy savings. The proposed methodology will be applied to five state-of-the-art energy-efficient technologies in the carbon fiber composites sector, with technology data obtained from the Department of Energy's 2016 bandwidth study. Because the importance weights used in estimating the Bass curve parameters are subjective, a sensitivity analysis will be performed on the weights to obtain a range of parameters for each technology. The potential energy savings for each technology and the rate at which each technology is adopted in the sector are quantified and used to identify the technologies which offer the greatest cumulative sector-level energy savings over a period of 20 years. Preliminary analysis indicates that relatively simple technologies, such as efficient furnaces, will be adopted more quickly and result in greater cumulative energy savings compared to more complex technologies that require process retrofitting, such as advanced control systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Remote Fiber Based Velocimeter For Interface Strength Measurements

The understanding of the performance of nuclear reactor plate fuels is essential when developing new fuel systems. The condition of pre and post irradiated plate fuels must be characterized effectively and efficiently prior to irradiation and then post irradiation within a high rad environment. The post characterization work must be performed remotely and in an environment hostile to instrumentation. Laser based characterization methods provide the capability to be remote and robust within a hot-cell environment. Laser based characterization can provide high spatial resolution appropriate for scanning and imaging large areas. The INL is currently developing a laser shock system for Post Irradiation Examination (PIE) station for use in the Hot Fuel Examination Facility (HFEF) at the INL. The laser shock system is designed to characterize fuel to cladding and cladding to cladding interface strength. The laser shock-technique induces large amplitude shock waves to mechanically characterize interfaces such as the fuel-clad interface. The shock wave propagates as a compressional wave through the fuel plate to the free (unconfined) backside surface and is reflected back through the test plate as a rarefaction (tensile) wave. This rarefaction wave is the physical mechanism that produces internal delamination failure. The focus or this paper is on the accurate measurement of surface velocity to quantify the amount of energy traveling through the interfaces to the back surface of the fuel plate. The original fiber based velocimeter design was biased by parasitic back reflections. This paper will discuss the discovery of the back-reflection issue and the design changes to resolve the issue. Supporting data will be presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Measuring the usability of appliance controls

A “smart” device will remain efficient only as long as the settings and other parameters allow it to be. Thus, the degree of usability is becoming an element of energy efficiency similar to other physical characteristics. We developed and tested a procedure to quantify the usability of thermostats. The procedure assumes that usability can be represented by a user’s ability to accomplish a set of tasks. Thirty one subjects were tested in their ability to accomplish six essential tasks on programmable thermostats. The tests revealed a wide variation in the subjects’ ability to accomplish the same task on different thermostats. Thus it was possible to discern thermostats that were more effective than others. We created a metric based on data that are easy to collect and unambiguous that appears to reflect the usability of a task. Metrics from different tasks can be added and an overall usability “score” calculated. This approach, as well as the metric, can be applied to other devices where poor usability may impede energy-saving behaviour.

Meier, A↗