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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A Wolter imager on the Z machine to diagnose warm x-ray sources

A new Wolter x-ray imager has been developed for the Z machine to study the emission of warm (>15 keV) x-ray sources. A Wolter optic has been adapted from observational astronomy and medical imaging, which uses curved x-ray mirrors to form a 2D image of a source with 5 × 5 × 5 mm 3 field-of-view and measured 60-300-μm resolution on-axis. The mirrors consist of a multilayer that create a narrow bandpass around the Mo Kα lines at 17.5 keV. Here, we provide an overview of the instrument design and measured imaging performance. In addition, we present the first data from the instrument of a Mo wire array z-pinch on the Z machine, demonstrating improvements in spatial resolution and a 350-4100× increase in the signal over previous pinhole imaging techniques.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Accuracy, criteria, and clinical significance of visual assessment on diffusion-weighted imaging and apparent diffusion coefficient quantification for diagnosing acute appendicitis

Purpose: To assess the accuracy, criteria, and clinical significance of diffusion-weighted imaging (DWI) signal intensity and apparent diffusion coefficient (ADC) quantification for diagnosing acute appendicitis. Methods: Fifty-one patients with right lower abdominal pain [uncomplicated appendicitis (n = 25), complicated appendicitis (n = 10), and non-appendicitis (n = 16)] who underwent MR examination were enrolled in this retrospective study. Two radiologists independently measured appendiceal diameter and wall thickness. They assessed whether a wall defect, an abscess, extraluminal air, or an appendicolith was present on axial T2WI; evaluated intensity on DWI using a 5-point scale; and determined the ADC values of the appendix and peri-appendiceal tissue. Statistical analysis was performed to assess imaging findings for the diagnosis of appendicitis and complicated appendicitis. Cut-off values were determined using receiver operating characteristic analysis. Results: For diagnosing acute appendicitis, the accuracy improved from 78.4% using only T2WI to 86.3% using combined T2WI and DWI for reader 1 and from 82.4 to 86.3% for reader 2. For the appendix, the cut-off ADC values that diagnosed appendicitis were 1.41 × 10{sup −3} and 1.26 × 10{sup −3} mm{sup 2}/s with accuracies of 78.4% and 76.5%, respectively. For the peri-appendiceal tissue, these values of 1.03 × 10{sup −3} and 0.91 × 10{sup −3} mm{sup 2}/s differentiated between uncomplicated and complicated appendicitis with an accuracy of 97.1%. Conclusions: Combined DWI and T2WI provided high accuracy for diagnosing appendicitis. The inflamed appendix had lower ADC value than the normal appendix. The peri-appendiceal tissue presenting low ADC value was a notable finding of complicated appendicitis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

End-to-End Simulations of a 3.4-Meter Detector Wall for Neutron-Diagnosed Subcritical Experiments

The Nevada National Security Site, together with Los Alamos National Laboratory and Lawrence Livermore National Laboratory, is developing a novel diagnostic to measure the reactivity of subcritical experiments. This capability is known as neutron-diagnosed subcritical experiments. The decay of the fission gamma rays from the neutron-interrogated subcritical experiment is measured as a function of time with a large (~3-meter diameter) detector wall consisting of 151 individual detector pixels. The data from this current mode measurement inform the neutron multiplication factor, keff, and thus the relative reactivity of the subcritical experiment. The Nevada National Security Site developed the Gamma Array Simulation Toolkit initially to help inform the design of the individual detector pixels and the 3.4-meter diameter detector wall to be fielded as part of neutron-diagnosed subcritical experiments. This toolkit is now being used to simulate and predict the performance of the final design of the individual detector pixels and the aggregate detector wall. Additionally, key detector characteristics evaluated from these simulations include impulse response, pulse height spectrum, number of photoelectrons per MeV, detector efficiency, and cross talk between detector pixels. Collectively, the results of these simulations inform how well the fission gamma ray die-off distribution from a neutron-diagnosed subcritical experiment measurement can be resolved. This is critical to determining the relative reactivity of the experiment. Furthermore, the Gamma Array Simulation Toolkit can be used to aid in the analysis of the experimental data from a neutron-diagnosed subcritical experiment measurement once the simulation has been benchmarked.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

End-to-End Simulations of a 3.4-Meter Detector Wall for Neutron-Diagnosed Subcritical Experiments

The Nevada National Security Site, together with Los Alamos National Laboratory and Lawrence Livermore National Laboratory, is developing a novel diagnostic to measure the reactivity of subcritical experiments. This capability is known as neutron-diagnosed subcritical experiments. The decay of the fission gamma rays from the neutron-interrogated subcritical experiment is measured as a function of time with a large (~3-meter diameter) detector wall consisting of 151 individual detector pixels. The data from this current mode measurement inform the neutron multiplication factor, keff, and thus the relative reactivity of the subcritical experiment. The Nevada National Security Site developed the Gamma Array Simulation Toolkit initially to help inform the design of the individual detector pixels and the 3.4-meter diameter detector wall to be fielded as part of neutron-diagnosed subcritical experiments. This toolkit is now being used to simulate and predict the performance of the final design of the individual detector pixels and the aggregate detector wall. Key detector characteristics evaluated from these simulations include impulse response, pulse height spectrum, number of photoelectrons per MeV, detector efficiency, and cross talk between detector pixels. Collectively, the results of these simulations inform how well the fission gamma ray die-off distribution from a neutron-diagnosed subcritical experiment measurement can be resolved. This is critical to determining the relative reactivity of the experiment. Furthermore, the Gamma Array Simulation Toolkit can be used to aid in the analysis of the experimental data from a neutron-diagnosed subcritical experiment measurement once the simulation has been benchmarked.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

{sup 68}Ga-PSMA-11 PET/CT in newly diagnosed prostate cancer: diagnostic sensitivity and interobserver agreement

Purpose: To determine the diagnostic sensitivity and interobserver agreement of Gallium 68-prostate-specific membrane antigen positron emission tomography/computed tomography ({sup 68}Ga-PSMA-11 PET/CT) imaging for diagnosis and staging of patients with newly diagnosed prostate cancer (PC). Materials and methods: One hundred and seventy-three men (mean age, 68 ± 7.7 years; range 46–84 years) with newly diagnosed, untreated PC were enrolled in this prospective study between January 2017 and August 2018. All patients underwent a {sup 68}Ga-PSMA-11 PET/CT examination. For each patient, we determined the disease stage, the Gleason score, and the maximum standardized uptake value (SUVmax) for primary prostatic tumor and extraprostatic metastases. The diagnostic sensitivity and interobserver agreement of {sup 68}Ga-PSMA-11 PET/CT for diagnosis and staging of PC were established by histopathology as the reference standard. Results: {sup 68}Ga-PSMA-11 PET/CT examinations were interpreted as positive for PC in 166 of 173 patients (101 patients had primary prostatic tumor only, two patients had extraprostatic metastases only and 63 patients had combined lesions). The sensitivity of {sup 68}Ga-PSMA-11 PET/CT examination in the diagnosis of PC was 96%. {sup 68}Ga-PSMA-11 PET/CT produced a significant change of stage in 28.6% patients with an upstage in 17.9% patients and a downstage in 10.7% patients. The interobserver agreements were almost good to perfect (k = 0.63–0.89) for visual image interpretation, SUVmax measurement, and tumor staging. Conclusion: {sup 68}Ga-PSMA-11 PET/CT is a valuable tool with high diagnostic sensitivity (96%) and high reproducibility for diagnosis and staging of patients with newly diagnosed PC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Medical diagnoses using three-way fuzzy concept lattice and their Euclidean distance

Searching the closest symptoms of a particular disease in the given patient is a major concern for medical diagnoses expert. In most cases, this problem arises due to large number of incomplete, uncertain, or inconsistent information generated in medical diagnoses data set. Recently, some of the researchers tried to pay attention towards precise measurement of uncertainty and vagueness in medical data set using the properties of applied abstract algebra. In this process, researchers noticed that calculus of three-way decision space is more useful to characterize the uncertainty and vagueness in medical data set based on truth, indeterminacy, and falsity membership-values. However, searching some relevant query based on user requirement to diagnoses the disease is a major issue in three-way decision space. To encounter this problem, current paper tried to analyze the medical data set using the properties of single-valued neutrosophic graph-based concept lattice. In addition, another method is proposed to select some of the interesting three-way fuzzy concepts at user-defined granulation for their computed Euclidean distance with an illustrative example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Tick bite frequency, prevention practices and Lyme disease diagnoses among U.S. Hispanic survey respondents

Abstract Tick bite prevention practices, knowledge of Lyme disease (LD) symptoms and transmission, and patterns of LD diagnoses among Hispanic persons have been reported but not comprehensively evaluated. In 2014, CDC examined questions from a prospective nationwide survey of U.S. Hispanic adults conducted via the Offerwise QueOpinas panel regarding ticks and LD. From October to November, a total of 2,649 surveys were released and 1,006 completed surveys returned. Overall, 44% of respondents reported routinely practising at least one form of personal protection against tick bites, and wearing repellent was the most commonly reported method (29%). Approximately 6% of respondents reported a tick bite for either themselves or someone in their household during the previous 12 months. An individual or household diagnosis of LD in the previous year was reported by 2% of respondents, with the highest proportion of diagnoses reported by respondents from high LD incidence states. The annual incidence of healthcare provider‐diagnosed LD in the survey population was higher than national surveillance estimates for reported LD among U.S. Hispanic persons during 2000–2013. As annual incidence of LD continues to increase, it is important to ensure equitable access to information about LD, including disease transmission, manifestations, and prevention recommendations. Results from this survey can help inform public health outreach focused on effective tick bite prevention methods and early recognition of LD.

Beck, Alyssa↗
DOE OSTI2021

End-to-End Simulations of a 3.4-Meter Detector Wall for Neutron-Diagnosed Subcritical Experiments

The Nevada National Security Site, together with Los Alamos National Laboratory and Lawrence Livermore National Laboratory, is developing a novel diagnostic to measure the reactivity of subcritical experiments. This capability is known as neutron-diagnosed subcritical experiments. The decay of the fission gamma rays from the neutron-interrogated subcritical experiment is measured as a function of time with a large (~3-meter diameter) detector wall consisting of 151 individual detector pixels. The data from this current mode measurement inform the neutron multiplication factor, keff, and thus the relative reactivity of the subcritical experiment. The Nevada National Security Site developed the Gamma Array Simulation Toolkit initially to help inform the design of the individual detector pixels and the 3.4-meter diameter detector wall to be fielded as part of neutron-diagnosed subcritical experiments. This toolkit is now being used to simulate and predict the performance of the final design of the individual detector pixels and the aggregate detector wall. Key detector characteristics evaluated from these simulations include impulse response, pulse height spectrum, number of photoelectrons per MeV, detector efficiency, and cross talk between detector pixels. Collectively, the results of these simulations inform how well the fission gamma ray die-off distribution from a neutron-diagnosed subcritical experiment measurement can be resolved. This is critical to determining the relative reactivity of the experiment. Furthermore, the Gamma Array Simulation Toolkit can be used to aid in the analysis of the experimental data from a neutrondiagnosed subcritical experiment measurement once the simulation has been benchmarked.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Using discrete Bayesian networks for diagnosing and isolating cross-level faults in HVAC systems

Fault detection and diagnosis (FDD) technologies are critical to ensure satisfactory building performance, such as reducing energy wastes and negative impacts on occupant comfort and productivity. Existing FDD technologies mainly focus on component-level FDD solutions, which could lead to mis-diagnosis of cross-level faults in heating, ventilating, and air-conditioning (HVAC) systems. Cross-level faults are those faults that occur in one component or subsystem, but cause operational abnormalities in other components or subsystems, and result in a building level performance degradation. How to effectively diagnose the root cause of a cross-level fault is the focus of this study. Here, this paper presents a novel discrete Bayesian Network (DisBN)-based method for diagnosing cross-level faults in an HVAC system commonly used in commercial buildings. A two-level DisBN structure model is developed in this study. The parameters used in the DisBN model are obtained either from expert knowledge or through machine-learning strategies from normal system operation data. Meanwhile, the probability parameters are discretized to incorporate the uncertainties associated with typical expert knowledge. Thus, the developed DisBN method addresses the challenges many other BN based FDD methods face, i.e., the lack of fault data for BN parameter training. The developed DisBN represents causal relationships between a fault and its cross-level system impacts (i.e., fault symptoms or fault indicators) by considering how fault impacts propagate across different levels in an HVAC system. A weather and schedule information-based Pattern Matching (WPM) method is employed to automatically create WPM baseline data sets for each incoming real time snapshot data from the building systems. Consequently, BN inference and real-time diagnostics are achieved by comparing incoming snapshot data and the WPM baseline data set. The proposed method is evaluated using experimental fault data collected in a campus building. Fault diagnosis results demonstrate that the WPM-DisBN method is effective at locating the root causes of cross-level faults in an HVAC system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Comparison of Expert Vocabulary Usage Patterns Between Mental Health and Nonmental Health Clinicians When Diagnosing Pediatric Anxiety Disorders

Objective: To compare the utilization patterns of expert vocabulary (EVo) in diagnosing pediatric anxiety between mental health and non-mental health clinical notes from electronic health records to understand the role of Evo in informing classification and decision-making in anxiety diagnoses. Study design: We conducted a retrospective study using a cohort less than age 25 from Cincinnati Children's Hospital including 897 685 patients with 61 586 446 notes. We analyzed EVo, collected from mental health clinicians, in both mental and nonmental health notes. We compared classification accuracy using EVo-based patient-level embedding from all clinical notes, mental-health notes, and nonmental health notes for 2 tasks: 1) pre-vs postdiagnosis anxiety patients, and 2) prediagnosis anxiety vs nonanxiety patients. Results: EVo usage was highest in prediagnosis anxiety, lower in nonanxiety, and lowest in post-diagnosis. Classification models using EVo features from all, mental-health, and non-mental health notes showed similar F1 scores for prediagnosis anxiety (0.70 ± 0.2 for 2 categories). For anxiety vs nonanxiety classification, all clinical and nonmental health notes had better F1 scores than mental-health notes (above 0.90 for 3 categories). There was a notable difference in class-wise performance across both tasks. Conclusions: There are significant differences in anxiety EVo use between mental health and nonmental health clinicians. Despite less anxiety-specific terminology, non-mental health notes still captured key aspects of patient presentations, emphasizing the importance of including all clinicians' notes in analysis. EVo's utility for anxiety classification is most effective in prediagnostic phases, suggesting the need for a dedicated diagnostic lexicon and further study before incorporating EVo into classification models.

feature engineering↗
DOE OSTI2021

Unabsorbed light beamlets for diagnosing coronal density profiles and absorption nonuniformity in direct-drive implosions on OMEGA

Laser light scattered from a target is the most-direct measurement for diagnosing laser absorption in a direct-drive implosion. The 3ωGOI (gated optical imager) beamlets diagnostic images unabsorbed light from all 60 OMEGA beams as distinct “beamlet” spots for each beam. The implosion can be diagnosed using the position and intensity of these beamlets. The position of each beamlet in the image is determined by refraction and can be used to fit the coronal plasma density profile of the implosion. The inferred plasma density profiles are comparable to profiles predicted by the 1-D hydrodynamics code LILAC but suggest the predictions underestimate the density farther out in the corona. The intensity of light in each spot depends on the cumulative effects of absorption and cross-beam energy transfer along the beamlet’s path through the corona. Furthermore, the measured variation in intensity and polarization between similar spots indicates that absorption during OMEGA implosions is less uniform than previously known.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Diagnosing low-mode (ℓ < 6) and mid-mode (6 ≤ ℓ ≤ 60) asymmetries in the post-stagnation phase of laser-direct-drive deuterium–tritium cryogenic implosions on OMEGA

Low- and mid-mode perturbations are possible candidates for performance limitations in cryogenic direct-drive implosions on the OMEGA laser at the Laboratory of Laser Energetics. Simulations with a 3D hydrocode demonstrated that hotspot imagers do not show evidence of the shell breakup in the dense fuel. However, these same simulations revealed that the low- and mid-mode perturbations in the dense fuel could be diagnosed more easily in the post-stagnation phase of the implosion by analyzing the peak in the x-ray emission limb at the coronal–fuel interface than before or at the stagnation phase. In experiments, the asymmetries are inferred from gated images of the x-ray emission of the implosion by using a 16-pinhole array imager filtered to record x-ray energies >800 eV and an x-ray framing camera with 40-ps time integration and 20-μm spatial resolution. Furthermore, a modal analysis is applied to the spatial distribution of the x-ray emission from deuterium and tritium cryogenic implosions on OMEGA recorded after the bang time to diagnose the low- and mid-mode asymmetries, and to study the effect that the beam-to-target ratio (Rb/Rt) has on the shell integrity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Scattered-light uniformity imager for diagnosing laser absorption asymmetries on OMEGA

Light scattered from a target is the most-direct measurement for diagnosing laser absorption in a direct-drive implosion. Observations from OMEGA implosions show much larger scattered-light asymmetries than predictions. A new instrument has been developed to absolutely measure the scattered-light intensity and nonuniformity for the purpose of diagnosing the asymmetry. The scattered-light uniformity imager (SLUI) diagnostic records the variation in scattered-light intensity over a transmission diffuser using a charge-coupled device (CCD)/lens assembly. At the standard operating position, an 11.3° (f/2.5) cone of light is collected. A stray light baffle, debris shield, and antireflection absorbing filter are also incorporated into the diagnostic payload inserted into the target chamber. The imaging parts of the diagnostic (light baffle, vacuum window, filters, lens, and CCD camera) are located outside the target chamber. Five SLUIs have been built and deployed in OMEGA’s ten-inch manipulator diagnostic ports, covering almost 5% of the emission surface, enabling an absolute scattered-light measurement should be within a few percent of the global average. Each SLUI system is calibrated offline, providing absolute scattered-light intensity measurements. Based on the measured point spread function, each diffuser plate image contains over 20 000 independent scattered-light absolute-intensity measurements of the variation over the collection cone. SLUI provides a platform to study scattered light and absorption asymmetries, and their possible sources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Completion Effects on Diagnosing Multistage Facture Treatments with Distributed Temperature Sensing

Summary Distributed temperature sensing (DTS) is a valuable tool to diagnose multistage hydraulic fracture treatments. When a stage interval is shut in, the clusters that take more fluid during pumping warm up more slowly. Therefore, the fluid volume injected into each cluster can be quantitatively interpreted by numerical inversion of the warm-back temperature behavior. This general concept assumes that the different warm-back behavior is controlled by only the injected fluid volume; however, recent observations of DTS data indicate that completion configurations significantly influence the warm-back behavior. This paper investigates the completion effects on the DTS interpretation. In ideal conditions, when a stage is fractured, the upstream stage intervals should show an almost uniform temperature that is close to the injected fluid temperature. This is due to the high fluid velocity of injected fluid in the wellbore, and the upstream intervals have not been perforated (noncommunicating intervals), so the only heat transfer is heat conduction between the wellbore fluid and the surrounding reservoir. But the field DTS data show considerably irregular variations in temperature along the upstream stage intervals. These variations are caused by the completion effects. The nonuniform temperature profile is caused by different heat transfer behavior induced by completion hardware along the production casing string, such as joints, clamps, and blast protectors, and by the sensing cable location in the cement, as well as the cement quality. Because the varying heat transfer behavior impacts the warm-back behavior as well as the temperature profile, the completion effects need to be considered in DTS interpretation. A method of DTS interpretation considering the completion effects to diagnose multistage fracture treatments was developed. Because the heat transfer between a wellbore and a reservoir depends on the overall heat transfer coefficient describing heat conduction through the completion in a forward model, this parameter needs to be tuned all along the wellbore. To calibrate the completion effect, the temperature inversion is conducted using the temperature measured at a stage interval that is upstream of a stage interval currently being treated. Because the interpreted stage interval is not perforated at that time, the thermal behavior at the noncommunicating interval is governed by only the heat conduction through the completion environment. Once the effective values of the overall heat transfer coefficient are estimated along the interpreted stage interval, they can be assumed to be constant physical parameters. Then, the fluid volume distribution is interpreted by using the effective overall heat transfer coefficient profile along each interval. This study provides a field application of the developed interpretation method. The new interpretation method provides more accurate diagnosis of fracture treatments by DTS interpretation.

Engineering↗
DOE OSTI2022

Diagnosing Barren Plateaus with Tools from Quantum Optimal Control

Variational Quantum Algorithms (VQAs) have received considerable attention due to their potential for achieving near-term quantum advantage. However, more work is needed to understand their scalability. One known scaling result for VQAs is barren plateaus, where certain circumstances lead to exponentially vanishing gradients. It is common folklore that problem-inspired ansatzes avoid barren plateaus, but in fact, very little is known about their gradient scaling. In this work we employ tools from quantum optimal control to develop a framework that can diagnose the presence or absence of barren plateaus for problem-inspired ansatzes. Such ansatzes include the Quantum Alternating Operator Ansatz (QAOA), the Hamiltonian Variational Ansatz (HVA), and others. With our framework, we prove that avoiding barren plateaus for these ansatzes is not always guaranteed. Specifically, we show that the gradient scaling of the VQA depends on the degree of controllability of the system, and hence can be diagnosed through the dynamical Lie algebra $\mathfrak{g}$ obtained from the generators of the ansatz. We analyze the existence of barren plateaus in QAOA and HVA ansatzes, and we highlight the role of the input state, as different initial states can lead to the presence or absence of barren plateaus. Taken together, our results provide a framework for trainability-aware ansatz design strategies that do not come at the cost of extra quantum resources. Moreover, we prove no-go results for obtaining ground states with variational ansatzes for controllable system such as spin glasses. Our work establishes a link between the existence of barren plateaus and the scaling of the dimension of $\mathfrak{g}$.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Social Disparities of Pain and Pain Intensity Among Women Diagnosed With Early Stage Breast Cancer

Background: Breast cancer is one of the most commonly diagnosed cancers among women in the United States and pain is the most common side effect of breast cancer and its treatment. Yet, the relationships between social determinants of pain and pain experience/intensity remain under-investigated. We examined the associations between social determinants of pain both at the individual level and the neighborhood level to understand how social conditions are associated with pain perception among early stage breast cancer patients. Methods: We conducted integrated statistical analysis of 1,191 women with early stage breast cancer treated at a large cancer center in Memphis, Tennessee. Combining electronic health records, patient-reported data and census data regarding residential address at the time of first diagnosis, we evaluated the relationships between social determinants and pain perception. Pain responses were self-reported by a patient as a numerical rating scale score at the patient’s initial diagnosis and follow-up clinical visits. We implemented two sets of statistical analyses of the zero-inflated Poisson model and estimated the associations between neighborhood poverty prevalence and breast cancer pain intensity. After adjustment for demographic characteristics, cancer stage, and chemotherapy, pain perception was significantly associated with poverty and blight level of the neighborhood. Results: Among women living in the highest-poverty areas, the odds of reporting pain were 2.48 times higher than those in the lowest-poverty area. Women living in the highest-blight area had 5.43 times higher odds of reporting pain than those in the lowest-blight area. Neighborhood-level social determinants were significantly associated with pain intensity among women diagnosed with early-stage breast cancer. Conclusions: Distressed neighborhood conditions are significantly associated with higher pain perception. Breast cancer patients living in socio-economically disadvantaged neighborhoods and in poor environmental conditions reported higher pain severity compared to patients from less distressed neighborhoods. Therefore, post-diagnosis pain treatment design needs to be tailored to the social determinants of the breast cancer patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Technical note: Recommendations for diagnosing cloud feedbacks and rapid cloud adjustments using cloud radiative kernels

Abstract. The cloud radiative kernel method is a popular approach to quantify cloud feedbacks and rapid cloud adjustments to increased CO2 concentrations and to partition contributions from changes in cloud amount, altitude, and optical depth. However, because this method relies on cloud property histograms derived from passive satellite sensors or produced by passive satellite simulators in models, changes in obscuration of lower-level clouds by upper-level clouds can cause apparent low-cloud feedbacks and adjustments, even in the absence of changes in lower-level cloud properties. Here, we provide a methodology for properly diagnosing the impact of changing obscuration on cloud feedbacks and adjustments and quantify these effects across climate models. Averaged globally and across global climate models, properly accounting for obscuration leads to weaker positive feedbacks from lower-level clouds and stronger positive feedbacks from upper-level clouds while simultaneously removing a mostly artificial anti-correlation between them. Given that the methodology for diagnosing cloud feedbacks and adjustments using cloud radiative kernels has evolved over several papers, and obscuration effects have only occasionally been considered in recent papers, this paper serves to establish recommended best practices and to provide a corresponding code base for community use.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Results of Three Neutron Diagnosed Subcritical Experiments

Neutron diagnosed subcritical experiments (NDSEs) aim to measure the fission chain decay of subcritical test objects initiated by neutrons from an external source. The ultimate goal of future NDSEs is to make such measurements on dynamic subcritical objects as they are imploded. In this work, as a step toward that goal, we made measurements on three static subcritical assemblies containing highly enriched uranium. Specifically, we measured the die-off of both fission gamma rays and neutrons, with nanosecond resolution over several hundred microseconds, relative to the emission time of neutrons from a source in close proximity to the subcritical objects. Additionally, as simulations are expected to play a key role in interpreting future NDSEs, we compared our data to detailed MCNP® calculations. There was good agreement between the data and MCNP over die-off times expected to be most important to future NDSEs, but there were significant differences at both earlier and later times. We attempted to reconcile these differences by several changes to the simulations. In particular, we found that reducing the 235U(n,n’) cross section to 80% of the current ENDF7.1 evaluation resulted in much better agreement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗