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At least 685 records · Page 38

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NASA NTRS2019

Diagnosing Bias in Modeled Soil Moisture/runoff Coefficient Correlation Using the SMAP Level 4 Soil Moisture Product

The physical parameterization of key processes in land surface models (LSMs) remains uncertain, and new techniques are required to evaluate LSM accuracy over coarse spatial scales. Given the role of soil moisture in the partitioning of surface water fluxes (between infiltration, runoff and evapotranspiration), surface soil moisture (SSM) estimates represent an important observational benchmark for such evaluations. Here, we apply SSM estimates from the NASA Soil Moisture Active Passive Level 4 product (SMAP_L4) to diagnose bias in the coupling between SSM and surface runoff for multiple Noah-Multiple Physics (Noah-MP) LSM parameterization cases. Results demonstrate that Noah-MP surface runoff parameterizations often underestimate the coupling strength between pre-storm SSM and the event-scale runoff coefficient (RC; defined as the ratio between event-scale streamflow and precipitation volumes). This bias squanders RC information contained in pre-storm SSM and reduces RC estimation skill. Such bias can be quantified against an observational benchmark calculated using streamflow observations and SMAP_L4 SSM and applied to explain a substantial fraction of the observed basin-to-basin (and case-to-case) variability in the skill of event-scale Noah-MP RC estimates. Based on this concept, a novel case selection strategy for ungauged basins is introduced and demonstrated to successfully identify poorly performing Noah-MP parameterization cases.

SSM↗

NASA NTRS2019

CloudSat Bias on Falling Snow Estimates Over the Daylight Only Operational Period (2012-2019)

Falling snow is a key component for the global atmospheric, hydrological and energy cycles, and its retrieval from space-based observations represents the best current capability to evaluate it globally. The Global Precipitation Measurement (GPM) Mission Core Observatory, launched in 2014, together with its constellation sensors, can provide quasi-global precipitation estimates every 30 minutes (for level 3 products). Evaluation and validation efforts for such products are crucial, and for global evaluations, one of the most suitable instruments is the Cloud Profiling Radar (CPR) on board CloudSat, which is sensitive to light rain and falling snow. However, due to a battery anomaly in 2011, during its period of overlapping observations with GPM the CPR has operated in a Daylight Only Operations mode (DO-Op) in which it makes measurements primarily during only the daylit portion of its orbit. The goal of this work is to estimate biases inherent in global snowfall amounts derived from CPR measurements due to this shift to DO-Op mode. We use CloudSat's snowfall measurements during its Full Operations (Full-Op) period from 2006 to 2010 to evaluate the impact DO-Op mode would have had during this period. Results indicate that omitting the nocturnal component of the diurnal cycle of snowfall has nonnegligible impact on snowfall amounts in some regions. The lack of nighttime data during DO-Op biases the latitudinally averaged mean snowfall rates as well as some regional values. Hemispheric differences in bias may be due to more pronounced diurnal variability in the northern hemisphere owing to more prevalent land surface versus the southern hemisphere. The results highlight the need to sample consistently with the CloudSat observations or to adjust snowfall estimates derived from CloudSat when using DO-Op data to evaluate other precipitation products.

Milani, Lisa↗

NASA NTRS2020

Comparing complex impedance and bias step measurements of Simons Observatory transition edge sensors

The Simons Observatory (SO) will perform ground-based observations of the cosmic microwave background (CMB) with several small and large aperture telescopes, each outfitted with thousands to tens of thousands of superconducting aluminum manganese (AlMn) transition-edge sensor bolometers (TESs). In-situ characterization of TES responsivities and effective time constants will be required multiple times each observing-day for calibrating time-streams during CMB map-making. Effective time constants are typically estimated in the field by briefly applying small amplitude square-waves on top of the TES DC biases, and fitting exponential decays in the bolometer response. These so-called “bias step” measurements can be rapidly implemented across entire arrays and therefore are attractive because they take up little observing time. However, individual detector complex impedance measurements, while too slow to implement during observations, can provide a fuller picture of the TES model and a better understanding of its temporal response. Here, we present the results of dark TES characterization of many prototype SO bolometers and compare the effective thermal time constants measured via bias steps to those derived from complex impedance data.

Nicholas F. Cothard↗

DOE OSTI2014

Comprehensive ecosystem model-experiment synthesis using multiple datasets at two temperate forest free-air CO2 enrichment experiments: model performance and compensating biases

Free Air CO2 Enrichment (FACE) experiments provide a remarkable wealth of data to test the sensitivities of terrestrial ecosystem models (TEMs). In this study, a broad set of 11 TEMs were compared to 22 years of data from two contrasting FACE experiments in temperate forests of the south eastern US the evergreen Duke Forest and the deciduous Oak Ridge forest. We evaluated the models' ability to reproduce observed net primary productivity (NPP), transpiration and Leaf Area index (LAI) in ambient CO2 treatments. Encouragingly, many models simulated annual NPP and transpiration within observed uncertainty. Daily transpiration model errors were often related to errors in leaf area phenology and peak LAI. Our analysis demonstrates that the simulation of LAI often drives the simulation of transpiration and hence there is a need to adopt the most appropriate of hypothesis driven methods to simulate and predict LAI. Of the three competing hypotheses determining peak LAI (1) optimisation to maximise carbon export, (2) increasing SLA with canopy depth and (3) the pipe model the pipe model produced LAI closest to the observations. Modelled phenology was either prescribed or based on broader empirical calibrations to climate. In some cases, simulation accuracy was achieved through compensating biases in component variables. For example, NPP accuracy was sometimes achieved with counter-balancing biases in nitrogen use efficiency and nitrogen uptake. Combined analysis of parallel measurements aides the identification of offsetting biases; without which over-confidence in model abilities to predict ecosystem function may emerge, potentially leading to erroneous predictions of change under future climates.

Walker, Anthony P↗

DOE OSTI2017

Bias by default? A means for a priori interface measurement

Systems have biases. Their interfaces naturally guide a user toward specific patterns of action. For example, modern word-processors and spreadsheets are both capable of taking word wrapping, checking spelling, storing tables, and calculating formulas. You could write a paper in a spreadsheet or could do simple business modeling in a word-processor. However, their interfaces naturally communicate which function they are designed for. Visual analytic interfaces also have biases. In this paper, we outline why simple Markov models are a plausible tool for investigating that bias and how they might be applied. We also discuss some anticipated difficulties in such modeling and touch briefly on what some Markov model extensions might provide.

Cottam, Joseph A.↗

DOE OSTI2020

Passive bias temperature compensation circuit module

A passive bias temperature compensation module for silicon photomultiplier, avalanche photodiodes and similar photodetectors that possess a moderately linear temperature coefficient of gain and that may be compensated by varying an applied bias voltage. The module includes an electrical circuit and a method for determining component values to provide a constant voltage source to stabilize the gain of one or more photodetector devices. A temperature sensor in the module is held in close thermal contact with the photodetector and a filter capacitor is electrically close to the photodetector. The module is based on the concept of temperature sensitive voltage division which is applicable to situations in which large numbers of photodetectors must be gain-compensated for temperature variations over a wide range while maintaining excellent gain matching. The passive bias temperature compensation method enables multiple photodetectors to share a single constant voltage supply without loss of matching performance.

42 ENGINEERING↗

DOE OSTI2022

Bias control for a memory device

Methods, systems, and devices for bias control for a memory device are described. A memory system may store indication of whether data is coherent. In some examples, the indication may be stored as metadata, where a first value indicates that the data is not coherent and a second value or a third value indicate that the data is coherent. When a processing unit or other component of the memory system processes a command to access data, the memory system may operate according to a device bias mode when the indication is the first value, and according to a host bias mode when the indication is the second value or the third value.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Bias control for a memory device

Walker, Dean↗

DOE OSTI2018

Breaking Through Historical Biases in Performance Assessments - 18056

Performance assessments (referred to as safety assessments internationally), which include mathematical modeling of natural and engineered systems for many hundreds and thousands of years, play an important role in decision-making for disposal of radioactive waste and cleanup of sites and facilities contaminated with radioactive material. These decisions can involve options costing hundreds of millions or even billions of dollars. Thus, it is critical to understand the underlying assumptions behind regulatory and technical aspects of these assessments to better understand and communicate the basis for decisions. Policy and technical biases deliberately built into early assessment approaches allowed safety margin to account for uncertainties known to be present, but not quantitatively assessed. Many of these biases (e.g., regulatory standards, human habits, effectiveness of waste forms, inadvertent intrusion assumptions, etc.) continue to exist in spite of advances in technical approaches and knowledge. These built-in biases, often not effectively communicated, can lead to misleading interpretation of results and potentially influence public confidence and costly regulatory decisions regarding the safety of a disposal facility or a closure action. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Estimating consistent biased source probabilities over arbitrary bins - 25621

This paper describes computational algorithms for estimating consistent biased source probabilities for the CADIS and FW-CADIS methods that are compatible with most of the general fixed-source capabilities of the MCNP continuous-energy transport code. The basic algorithm is a novel Monte Carlo sampling technique that enables the straightforward estimation of biased source probabilities over arbitrarily complex distribution trees. In recent work, a method has been developed for generating correct biased spatial source probabilities in the presence of rejection from an arbitrary number of geometry cells. Two numerical test problems that demonstrate the correctness of this new algorithm are presented, including a simplified model of a cooling water system with an N-17 neutron source. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2015

Analysis of an existing spent fuel pool storage rack using current practices and updated depletion bias and uncertainty values - 14458

In accordance with NRC Information Notice 2011-03: Nonconservative Criticality Safety Analysis for Fuel Storage, a US nuclear power plant reviewed their analysis of record (AOR) for possible nonconservative technical specifications related to the criticality safety of fuel storage. During this review, it was determined that some legacy fuel assemblies did not meet all the assumptions of the AOR, but did meet the plant Technical Specifications. The plant entered into an Operability Evaluation in order to evaluate the moderator temperature and boron concentration assumptions used in the AOR, as well as evaluate the impact of including additional biases and depletion uncertainties for the non-borated case. As this study was part of a response to the NRC Information Notice, a full assessment was not conducted. A re-analysis of the spent fuel rack in accordance with current practices was performed. This analysis used the bounding core conditions, and included all biases and depletion uncertainties. The results challenged the 10CFR50.68(b) requirement that 'the k-effective must remain below 1.0 (subcritical), at a 95 percent probability, 95 percent confidence level, if flooded with un-borated water'. Credits for additional reactivity offsets were then analyzed. Previous assumptions for the measurement uncertainty were evaluated and subsequently reduced. New values for the depletion bias and uncertainty were applied. More detailed, realistic modeling was used to remove conservatisms. The results showed that the storage racks met the 10CFR50.68(b) criteria for the un-borated case. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

The Case for and Against a Gadolinium Bias in SCALE: Round 2

The “Opening Arguments” for and against a gadolinium bias in SCALE were presented at the American Nuclear Society Annual Meeting in Philadelphia, Pennsylvania, in June, 2018. Some critical experiments included in the Oak Ridge National Laboratory Verified, Archived Library of Inputs and Data (VALID) indicate a significant bias as a function of gadolinium concentration. Other experiments indicate that no significant bias exists. The work presented here develops a larger suite of gadolinium-bearing benchmark models to further examine code, data, and benchmark performance. The new benchmark models have been reviewed for accuracy, but documentation and review for addition to the VALID library have not been completed. The problematic benchmarks included in VALID are HEU-SOL-THERM-014 and -016. These are two evaluations from a series of experiments from the Institute for Physics and Power Engineering (IPPE), Russia, documented in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The entire set of evaluations also includes HEU-SOL-THERM-015, -017, -018, -019, and -025. Each evaluation contains a different uranium concentration, and different configurations within each evaluation include different gadolinium concentrations. These 7 evaluations contain a total of 52 configurations and form the largest subset of experiments considered, and they allow for a more complete assessment of the performance of these benchmarks than has historically been possible using just the HEU-SOL-THERM-014 and -016 results. Additional solution experiments are considered, including MIX-SOL-THERM-006 and -007 and PU-SOL-THERM-034. MIX-SOL-THERM-007 is in the VALID library, whereas MIX-SOL-THERM-006 and PU-SOL-THERM-034 are not. The results for MIX-SOL THERM-007 have not shown a gadolinium trend. These mixed- and plutonium-fueled solutions include 28 configurations. Some experiments including solid fuel and solid gadolinium are also included. These experiments include highly enriched uranium (HEU) foils moderated with polyethylene in HEU-MET-THERM-010, -016, and -034, and low enriched uranium (LEU) pin arrays with gadolinia absorber rods in LEU-COMP THERM-036 and -043. A total 32 cases with solid fuel are included. The IPPE solution benchmarks show a fairly high degree of variability, but no clear trend as a function of gadolinium concentration can be observed. The mixed- and plutonium-fueled solutions show less variability than the HEU solutions and also no trend relative to gadolinium concentration. The solid-fueled experiments also show no trend as a function of gadolinium content. The entire set of benchmarks shows no clear trend on gadolinium content or the energy of the average neutron lethargy causing fission.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Bias Correction and Statistical Downscaling of Solar Radiation Using NA-CORDEX and the NSRDB

The current state-of-art for estimating long-term PV production uses long-term estimates of solar radiation variables, such as global horizontal irradiance (GHI), from previous years. This data is used in models such as the System Advisor Model (SAM) or PYSyst to predict annual production for a PV plant. This information is then used to estimate the production over the next 20 years (a typical plant lifetime) under the assumption that the variability over the current period is representative of the future. As the PV industry moves to extend plant lifetimes to 50 years the current assumptions of representativeness of weather may not be appropriate. This is especially true as our climate changes rapidly. To assess long-term PV production, future projections for solar radiation based on projected carbon emissions are readily available in regional and global climate models. However, climate model projections contain inherent biases that may need to be corrected for accurate analysis of future projections of climate variables. Several studies have analyzed projections of solar radiation for future years, however the accuracy of the model output compared to current and historic data has not been widely studied. Chen (2021) showed that available climate models do not accurately represent solar radiation in some cases, over-projecting GHI at the surface while under-projecting its obstructions, such as clouds and aerosols. This works aims to (1) increase understanding of the accuracy of solar radiation currently available in global and regional climate models and (2) implement bias correction through linear models based on reanalysis data compared to observed solar radiation. The latter aim will be conducted using available observed solar radiation data and modeled data from several regional climate models (RCMs). The bias correction method will be applied to projections of solar radiation resulting in a more accurate representation of the future of solar production.

climate data↗

DOE OSTI2025

Direct Measurement of Galaxy Assembly Bias using DESI DR1 Data

We report the first direct measurement of galaxy assembly bias, a critical systematic in cosmology, from the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. We introduce a novel, cosmology-independent method to measure the halo occupation distribution (HOD) by combining a state-of-the-art group catalog with weak gravitational lensing. For groups binned by total luminosity, we determine the galaxy occupation number $N_{\rm gal}$ from group-galaxy cross-correlations, while weak lensing constrains the average halo mass $M_h$. Applying this to a volume-limited sample at $z{\in}[0.05,0.2]$, we measure the dependence of HOD, $N_{\rm gal}(M_h)$, on large-scale overdensity $δ_{g}$. Focusing on the satellite galaxies, we find an assembly bias parameter of $Q_{\rm sat}{=}0.05{\pm}0.14$, a result consistent with zero and in tension with many empirical galaxy formation models. Our method provides a robust approach for characterizing galaxy assembly bias to achieve precision cosmology with DESI and future Stage-V surveys.

Shao, Zhiwei [Shanghai Jiaotong U.; Shanghai Jiao ↗

DOE OSTI2026

Graphical User Interface for a Biasing Board for the PSEC6

The PSEC6 is an application-specific integrated circuit (ASIC) designed for a readout system for a large area picosecond photodetector (LAPPD). The PSEC6 is currently in fabrication and pending testing. The testing system for the PSEC5, the previous iteration of the ASIC, required expensive and non-portable equipment, because the ASIC needs twelve adjustable reference voltages. The new testing system consists of an low-cost, open-source, cross-platform graphical user interface (GUI), a digital system, and a biasing board. The digital system is the interface between the GUI and biasing board, and can be implemented on a microcontroller or field-programmable gate array (FPGA). The biasing board contains twelve digital-to-analog converters (DACs) that are configurable via the GUI, which gives users the ability to write voltage values to all or specific DACs. The GUI was developed in C on Linux using the widget library GTK4 and cross-compiled for Windows compatibility. I2C and SPI protocols were implemented on an Adafruit Feather ESP32-S3 microcontroller to write commands to the DACs and PSEC6. A hardware implementation of the I2C protocol is in development on an FPGA. Since LAPPDs will be used by the Accelerator Neutrino Neutron Interaction Experiment (ANNIE) at Fermilab, the PSEC6 testing system in this internship project can potentially benefit future neutrino research. The project is relevant to the Department of Energy’s microelectronics mission, because the PSEC6 is an ASIC that will handle fast time signals arriving from the detector for readout. It also provided experience with building a cross-platform user interface, practicing digital design and implementation in hardware description language (HDL), and using simulations to inform new design iterations.

Guerrero, Sasha Camila [North Central Coll.]↗

DOE OSTI2023

Phosphorylation barcodes direct biased chemokine signaling at CXCR3

Chemokine receptors, a group of G protein-coupled receptors (GPCRs), interact with transducers such as G proteins, ß-arrestins, and GPCR kinases (GRKs). In the chemokine system, many chemokine agonists act as “biased agonists” that preferentially activate distinct signaling effectors when binding to the same receptor, resulting in distinct physiological effects. Although one third of FDA-approved drugs target GPCRs, there has been limited success in targeting the chemokine system. Currently, there is little evidence that differential receptor phosphorylation, or “phosphorylation barcodes,” direct these biased responses at chemokine receptors. To address this knowledge gap, we used mass spectrometry to demonstrate that chemokines of CXCR3 promote different ensembles of phosphorylation barcodes that are associated with differential activation of G proteins, ß-arrestins and GRKs. Chemokine stimulation also resulted in distinct changes throughout the kinome in global phosphoproteomic studies. Mutation of specific CXCR3 phosphosites altered ß-arrestin conformation and impacted ß-arrestin activation in molecular dynamics simulations. T-cells expressing phosphorylation-deficient CXCR3 mutants resulted in distinct agonist- and receptor-specific chemotactic and signaling profiles that were not completely explained by engagement of G proteins, ß-arrestins, and GRKs alone. In conclusion, our results directly link distinct GPCR phosphorylation patterns with non-redundant chemokine signaling (Figure 1).

CXCR3↗

DOE OSTI2022

Using lifetime of point defects for dislocation bias in bcc Fe

The interaction between dislocations and point defects is key to deformation processes and microstructural evolution of structural materials. In this work, we compute the lifetime of point defects to describe their interaction with dislocations. This approach can accurately account for the effects of the dislocation core and anisotropic defect dynamics to accumulatively determine the capture efficiency, sink strength, and dislocation bias at different temperatures and dislocation densities. Particularly, the absorption of point defects by straight screw and edge dislocations in a model bcc iron system is studied. The maximum swelling rates based on the obtained bias factors are in close agreement with a variety of experimental measurements, including both neutron and ion-irradiation data, especially when considering the survival fraction for point defects from displacement cascades. Further, this approach applies to many other processes and sinks, such as dislocation loops and interfaces, providing a powerful means to develop fundamental insights critical for improving radiation resistance and mechanical properties of structural materials through controlling defect interaction and evolution.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Coexistence of positive and negative exchange bias effect in Pr-doped NdCrO 3 samples

Positive and negative exchange bias effects are observed in Nd 1-x Pr x CrO 3 (0.00 ≤ x ≤ 1.00) polycrystalline samples. The shift of hysteresis loops, either opposing or following the direction of the field cooling, depends on the concentration of praseodymium. The temperature dependence of magnetization reveals a magnetic transition at T ≈ 220 K likely ascribed to the N é el temperature of Cr 3+ magnetic moments. The non-Kramer Pr 3+ ion seems to play an important role in the magnetic properties of this compound. In the range 0.00 ≤ x ≤ 0.60, all samples presented a decrease in the magnetization below TN and a clear compensation point. Pr-rich samples (x ≥ 0.70) show a paramagnetic-like behavior down to low temperatures. We report the most impressive result is the relation between reversal magnetization and the signal of exchange bias effect which seems be tuned by the Pr-doping.

36 MATERIALS SCIENCE↗