SEARCH · Engineering Papers

Results for “biasing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

DOE OSTI2021

In-Operando Characterization of P-I-N Perovskite Solar Cell Under Reverse Bias

A solar module is often exposed to a variety of intensity and uniformity illumination conditions throughout a day. In the field, objects or dirt can block light from hitting the module creating a partial shading event. When a partial shading event occurs the module power point tracking system will typically push the shaded cells into reverse bias in order to avoid the current loss from the other series connected illuminated cells. When perovskite solar cells are operated in reverse bias, electrochemical reactions can occur, leading to both reversible and irreversible performance losses. Excess holes generated by reverse bias cause and push the oxidation reaction of halide ions from the lattice to neutral halogen interstitial. Small interstitial halogen atoms can diffuse across the device and potentially move from the perovskite layer and into the transport layers, shifting the fermi levels in the devices. In this investigation we utilize cross-sectional kelvin probe atomic force microscopy to map the band energetics of perovskite solar cells during reverse bias. We observe a 150 meV decrease in the work function of the C 60 . This leads to a decrease of 150 mV and 4 mA/cm 2 in V oc and in J sc respectively. Finally, we discuss methods to prevent this irreversible degradation after a perovskite device is held under reverse bias.

fullerene↗

NASA NTRS1994

Sensor biases effect on the estimation algorithm for performance-seeking controllers

The performance-seeking-control algorithm (PSC) is designed to continuously optimize the performance of propulsion systems. The PSC uses a nominal model of the propulsion system and estimates, in flight, the engine deviation parameters (EDPs) characterizing engine deviations with respect to nominal conditions. In practice, the measurement biases (or model uncertainties) may prevent the estimated EDPs from reflecting the engine's actual off-nominal condition. This factor has a direct impact on the PSC scheme exacerbated by the open-loop character of the algorithm. An observability analysis shows that the biases cannot be estimated together with the EDPs. Moreover, biases and EDPs turn out to have equivalent effects on the measurements, leaving it undecided whether the estimated EDPs represent the actual engine deviation or whether they simply reflect the measurement biases. In this article, the effects produced by unknown measurement biases over the estimation algorithm are evaluated. This evaluation allows for identification of the most critical measurements for application of the PSC algorithm to an F100 engine.

F100 ENGINE↗

NASA NTRS2013

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1∕8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

extreme climate index↗

DOE OSTI2017

Validation and Bias Quantification of Criticality Safety Codes for SRNS Operations

The validation and bias quantification methods employed by the Criticality Safety Engineering group at Savannah River Nuclear Solutions are discussed. Both SCALE and MCNP are validated against benchmark experiments, where these benchmark models have been divided into subgroups representative of the types of fissile material operations at SRNS. A quantification of the bias is made for each subgroup for each code and the three methods employed for quantification are discussed. The bias information is employed directly in the establishment of the Upper Safety Limit (USL) value of the neutron multiplication factor when using standardized documented SRNS methods. A simple example of validation and bias quantification is given and the procedure for setting the USL using the derived bias information is also presented.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

The Role of Convective Gustiness in Reducing Seasonal Precipitation Biases in the Tropical West Pacific

Abstract Precipitation is an important climate quantity that is critically relevant to society. In spite of intense efforts, significant precipitation biases remain in most climate models. One pervasive and persistent bias found in many general circulation models occurs in the Tropical West Pacific where northern hemisphere summer‐time precipitation is often underestimated compared to observations. Using the DOE‐E3SM model, the inclusion of a missing process, convective gustiness, is shown to reduce those biases through a net increase in surface evaporation. Gustiness in surface wind fields is assumed to arise empirically in proportion to the intensity of convective precipitation. The increased evaporation can be treated as an increase in the moist static energy forcing into the atmosphere. A Normalized Gross Moist Stability (NGMS) framework (which characterizes the relationship between convective forcing and convective response) is used to explore the processes responsible for the precipitation bias, and the impact of the gustiness parameterization in reducing that bias. Because the NGMS of the Tropical West Pacific is less than unity in the E3SMv1 model, the increase in energy forcing amplifies the increase in precipitation to exceed that of the evaporative flux. Convective gustiness favors increased precipitation in regions where the resolved surface winds are weak and convection is present.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

The small-x gluon distribution in centrality biased pA and pp collisions

Here, the nuclear modification factor R pA (p T ) provides information on the small- x gluon distribution of a nucleus at hadron colliders. Several experiments have recently measured the nuclear modification factor not only in minimum bias but also for central pA collisions. In this paper we analyze the bias on the configurations of soft gluon fields introduced by a centrality selection via the number of hard particles. Such bias can be viewed as reweighting of configurations of small- x gluons. We find that the biased nuclear modification factor Q pA (p T ) for central collisions is above R pA (p T ) for minimum bias events, and that it may redevelop a “Cronin peak” even at small x . The magnitude of the peak is predicted to increase approximately like 1/A ⊥ ν , ν~0.6±0.1 , if one is able to select more compact configurations of the projectile proton where its gluons occupy a smaller transverse area A ⊥ . We predict an enhanced Q pp (p T )–1~1/(p T 2 ) ν and a Cronin peak even for central pp collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2014

Biased hypermutation occurred frequently in a gene inserted into the IC323 recombinant measles virus during its persistence in the brains of nude mice

Measles virus (MV) is the causative agent of measles and its neurological complications, subacute sclerosing panencephalitis (SSPE) and measles inclusion body encephalitis (MIBE). Biased hypermutation in the M gene is a characteristic feature of SSPE and MIBE. To determine whether the M gene is the preferred target of hypermutation, an additional transcriptional unit containing a humanized Renilla reniformis green fluorescent protein (hrGFP) gene was introduced into the IC323 MV genome, and nude mice were inoculated intracerebrally with the virus. Biased hypermutation occurred in the M gene and also in the hrGFP gene when it was inserted between the leader and the N gene, but not between the H and L gene. These results indicate that biased hypermutation is usually found in a gene whose function is not essential for viral proliferation in the brain and that the location of a gene in the MV genome can affect its mutational frequency. - Highlights: • Wild-type MV can cause persistent infections in nude mice. • Biased hypermutation occurred in the M gene. • Biased hypermutation occurred in an inessential gene inserted between the leader and the N gene.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Evaluation of the Causes of Wet-Season Dry Biases Over Amazonia in CAM5

This study investigates the causes of pronounced low precipitation bias over Amazonia in the Community Atmosphere Model version 5 (CAM5), a common feature in many global climate models. Our analysis is based on a suite of 3-day long hindcasts starting every day at 00Z from 1997 to 2012 and an AMIP simulation for the same period. The Amazonia dry bias appears by the second day in the hindcasts and is very robust for all the seasons with the largest bias magnitude during the wet season (December–February). The bias pattern and magnitude do not change much during different dynamical wind regimes on sub-seasonal time scales. We further classify the diurnal cycle of precipitation near the LBA sites from observations and hindcasts into three convective regimes: no precipitation, late afternoon deep convection, and nighttime deep convection. CAM5 can only simulate the late afternoon convective regime and completely fails to simulate the nighttime convection, which is mostly from propagating convective systems originating from remote locations. CAM5 mainly underestimates precipitation in the late afternoon and nighttime convective regimes, which occur during ~67% of wet season days and account for ~75% of accumulated precipitation amount in observations. The persistent warm temperature bias and slightly higher moisture below 850 mb likely trigger deep convection too frequently, resulting in an earlier but weaker rainfall peak in the diurnal cycle. Finally, shallow convection may not effectively transport moisture from boundary layer to the free atmosphere, which also leads to weaker deep convection events.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

The Convective-To-Total Precipitation Ratio and the “Drizzling” Bias in Climate Models

Overestimation of precipitation frequency and duration while underestimating intensity, that is, the “drizzling” bias, has been a long-standing problem of global climate models. Here we explore this issue from the perspective of precipitation partitioning. We found that most models in the Climate Model Intercomparison Project Phase 5 (CMIP5) have high convective-to-total precipitation (PC/PR) ratios in low latitudes. Convective precipitation has higher frequency and longer duration but lower intensity than non-convective precipitation in many models. As a result, the high PC/PR ratio contributes to the “drizzling” bias over low latitudes. The PC/PR ratio and associated “drizzling” bias increase as model resolution coarsens from 0.5° to 2.0°, but the resolution's effect weakens as the grid spacing increases from 2.0° to 3.0°. Some of the CMIP6 models show reduced “drizzling” bias associated with decreased PC/PR ratio. Thus, more reasonable precipitation partitioning, along with finer model resolution should alleviate the “drizzling” bias within current climate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Molecular mechanism of biased signaling at the kappa opioid receptor

The κ-opioid receptor (KOR) has emerged as an attractive drug target for pain management without addiction, and biased signaling through particular pathways of KOR may be key to maintaining this benefit while minimizing side-effect liabilities. As for most G protein-coupled receptors (GPCRs), however, the molecular mechanisms of ligand-specific signaling at KOR have remained unclear. To better understand the molecular determinants of KOR signaling bias, we apply structure determination, atomic-level molecular dynamics (MD) simulations, and functional assays. We determine a crystal structure of KOR bound to the G protein-biased agonist nalfurafine, the first approved KOR-targeting drug. We also identify an arrestin-biased KOR agonist, WMS-X600. Using MD simulations of KOR bound to nalfurafine, WMS-X600, and a balanced agonist U50,488, we identify three active-state receptor conformations, including one that appears to favor arrestin signaling over G protein signaling and another that appears to favor G protein signaling over arrestin signaling. These results, combined with mutagenesis validation, provide a molecular explanation of how agonists achieve biased signaling at KOR.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Intrinsic exchange biased anomalous Hall effect in an uncompensated antiferromagnet MnBi 2 Te 4

Achieving spin-pinning at the interface of hetero-bilayer ferromagnet/antiferromagnet structures in conventional exchange bias systems can be challenging due to difficulties in interface control and the weakening of spin-pinning caused by poor interface quality. In this work, we propose an alternative approach to stabilize the exchange interaction at the interface of an uncompensated antiferromagnet by utilizing a gradient of interlayer exchange coupling. We demonstrate this exchange interaction through a designed field training protocol in the odd-layer topological antiferromagnet MnBi 2 Te 4 . Our results reveal a remarkable field-trained exchange bias of up to ~ 400 mT, which exhibits high repeatability and can be easily reset by a large training field. Notably, this field-trained exchange bias effect persists even with zero-field initialization, presenting a stark contrast to the traditional field-cooled exchange bias. The highly tunable exchange bias observed in this single antiferromagnet compound, without the need for an additional magnetic layer, provides valuable insight into the exchange interaction mechanism. These findings pave the way for the systematic design of topological antiferromagnetic spintronics.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Understanding Peelle’s Pertinent Puzzle bias in generalized least squares regression through eigenspectrum analysis

Certain correlation structures in the data covariance matrix (DCM) used for generalized least squares (GLS) regression can result in biased estimates, commonly known in the field of nuclear data evaluation as Peele’s Pertinent Puzzle (PPP). This article introduces a generative, forward modeling framework within which the PPP bias is characterized through an eigenspectrum analysis of the DCM. This analysis highlights the root cause of the bias, generalizes the problem beyond the nuclear data field, and provides insight to the problem regimes where it can occur. What follows is an understanding that the bias can show up for any experimental neutron time-of-flight data for which systematic uncertainties have been quantified. Lastly, a discussion of the adaptation of cross validation approaches that require pre-whitening to incorporate the known ‘fix’ to the PPP bias in the GLS estimator.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Downscaling and bias-correction contribute considerable uncertainty to local climate projections in CMIP6

Abstract Efforts to diagnose the risks of a changing climate often rely on downscaled and bias-corrected climate information, making it important to understand the uncertainties and potential biases of this approach. Here, we perform a variance decomposition to partition uncertainty in global climate projections and quantify the relative importance of downscaling and bias-correction. We analyze simple climate metrics such as annual temperature and precipitation averages, as well as several indices of climate extremes. We find that downscaling and bias-correction often contribute substantial uncertainty to local decision-relevant climate outcomes, though our results are strongly heterogeneous across space, time, and climate metrics. Our results can provide guidance to impact modelers and decision-makers regarding the uncertainties associated with downscaling and bias-correction when performing local-scale analyses, as neglecting to account for these uncertainties may risk overconfidence relative to the full range of possible climate futures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Exchange bias switching in an antiferromagnet/ferromagnet bilayer driven by spin-orbit torque

Here the electrical manipulation of magnetization and exchange bias in antiferromagnet/ferromagnet thin films could be of use in the development of the next generation of spintronic devices. Current-controlled magnetization switching can be driven by spin-orbit torques generated in an adjacent heavy metal layer, but these structures are difficult to integrate with exchange bias switching and tunnelling magnetoresistance measurements. Here, we report the current-induced switching of the exchange bias field in a perpendicularly magnetized IrMn/CoFeB bilayer structure using a spin-orbit torque generated in the antiferromagnetic IrMn layer. By manipulating the current direction and amplitude, independent and repeatable switching of the magnetization and exchange bias field below the blocking temperature can be achieved. The critical current density for the exchange bias switching is found to be larger than that for CoFeB magnetization reversal. X-ray magnetic circular dichroism, polarized neutron reflectometry measurements and micromagnetic simulations show that a small net magnetization within the IrMn interface plays a crucial role in these phenomena.

42 ENGINEERING↗

DOE OSTI2024

Weak baselines and reporting biases lead to overoptimism in machine learning for fluid-related partial differential equations

One of the most promising applications of machine learning in computational physics is to accelerate the solution of partial differential equations (PDEs). The key objective of machine-learning-based PDE solvers is to output a sufficiently accurate solution faster than standard numerical methods, which are used as a baseline comparison. Here, we first perform a systematic review of the ML-for-PDE-solving literature. Out of all of the articles that report using ML to solve a fluid-related PDE and claim to outperform a standard numerical method, we determine that 79% (60/76) make a comparison with a weak baseline. Second, we find evidence that reporting biases are widespread, especially outcome reporting and publication biases. We conclude that ML-for-PDE-solving research is overoptimistic: weak baselines lead to overly positive results, while reporting biases lead to under-reporting of negative results. To a large extent, these issues seem to be caused by factors similar to those of past reproducibility crises: researcher degrees of freedom and a bias towards positive results. We call for bottom-up cultural changes to minimize biased reporting as well as top-down structural reforms to reduce perverse incentives for doing so.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Dislocation loop bias and void swelling in irradiated α-iron from mesoscale and atomistic simulations

Abstract Dislocation loops are ubiquitous in irradiated materials, and dislocation loop bias plays a critical role in void swelling. However, due to complicated interactions between dislocation loops and point defects, it is challenging to evaluate the bias factors of dislocation loops. Here, we determine the bias of sessile < 100 > loops in α-iron using a recently developed atomistic approach based on the lifetime of point defects. We establish a mechanistic understanding of the loop interaction based on the diffusion tendency of point defects near the loop core region. Mobile self-interstitial atoms tend to be absorbed from the edge of the loop, and a trapping region perpendicular to the habit plane of the loop exists. The dislocation loop bias is found to be substantially lower than those of straight dislocations in α-iron and should be included in swelling rate estimates. With the obtained sink strength and bias values, agreement is achieved with experimental results for both absolute values and temperature dependence.

Yu, Ziang↗

DOE OSTI2024

Emergence of exchange bias in van der Waals magnetic alloy CrxPt1−xTe2

Abstract Cr x Pt 1− x Te 2 is a recently developed van der Waals magnetic alloy noted for its stability under ambient conditions. Here, we report the emergence of an exchange bias effect in Cr x Pt 1− x Te 2 , without typical exchange bias sources such as an adjacent antiferromagnetic layer. We find that the exchange bias is present for x = 0.45 and absent for x = 0.35, which is correlated to the presence of a Cr modulation where the Cr concentration alternates each vdW layer (modulation period of 2 layers) for x ≥ 0.4. We perform Monte Carlo simulations utilizing exchange parameters from first-principles calculations, which recreate the exchange bias in hysteresis loops of Cr 0.45 Pt 0.55 Te 2 . From our simulations, we infer the source of exchange bias to be magnetic moments locked into free energy minima that resist magnetization reversal. This work presents a way to introduce desirable magnetic properties to van der Waals magnets.

Bailey-Crandell, Ryan↗

DOE OSTI2016

Kondo-like zero-bias conductance anomaly in a three-dimensional topological insulator nanowire

Zero-bias anomalies in topological nanowires have recently captured significant attention, as they are possible signatures of Majorana modes. Yet there are many other possible origins of zero-bias peaks in nanowires—for example, weak localization, Andreev bound states, or the Kondo effect. Here, we discuss observations of differential-conductance peaks at zero-bias voltage in non-superconducting electronic transport through a 3D topological insulator (Bi 1.33 Sb 0.67 )Se 3 nanowire. The zero-bias conductance peaks show logarithmic temperature dependence and often linear splitting with magnetic fields, both of which are signatures of the Kondo effect in quantum dots. As a result, we characterize the zero-bias peaks and discuss their origin.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗