Comments on the theory of the differential absorption experiment.
Modification to theory of differential absorption experiment involving Fresnel reflection coefficient of ionospheric irregularities
FRESNEL REFLECTOR↗
SEARCH · Engineering Papers
Results for “Differential Experiments”
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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DOE/NNSA Nuclear Criticality Safety Program – Brief Overview [Slides]
This presentation discusses nuclear data measurements and evaluation work for the NCSP. The objective of the NCSP is to provide measured and evaluated thermal, resonance, unresolved resonance, and fast region cross section data to address the priority NCSP nuclear data needs. It also discusses its vision which is to address multiple Nuclear Data 5- and 10-year goals and attributes identified in the NCSP. The intended final product is for rigorous ENDF/B evaluations to be produced from cross section measurements and analyses. It also discusses NCSP integral experiments and differential experiments in addition to NCSP support of SCALE in the future.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Phase jitter in a differential phase experiment.
Austin (1971) had concluded that, because of the 'phase jitter,' the differential phase experiment is useful over a more limited height range than the differential absorption experiment. Several observations are presented to show that this conclusion is premature. It is pointed out that the logical basis of the differential absorption experiment also requires that the O- and X-mode echoes, at a given time, come from the same irregularities. Austin's calculations are believed to contain a systematic error above 80 km.
Tanenbaum, B. S.↗
Differential drain resistance of field-effect transistors beyond pinch-off - A comparison between theory and experiment
Differential drain resistance calculation for junction field effect transistors
Kim, C.-K.↗
Design and Construction of a High-Resolution Hodoscope for the GlueX Experiment with High-Statistics Analysis of the p0, ¿, and ¿1 Photoproduction Cross Sections from the RadPhi Experiment
Differential cross sections for forward-angle photoproduction of p0, ¿, and ¿ 1 pseudoscalar mesons were measured using data from the RadPhi experiment conducted in Hall B at Jef ferson Lab. RadPhi utilized a tagged bremsstrahlung photon beam incident on a stationary 9Be target, with a detector system configured to trigger on a recoil proton in coincidence with multiple neutral showers in the calorimeter. Events were reconstructed and subjected to kinematic constraints, with background suppressed via sideband subtraction guided by Monte Carlo modeling of background contributions. Cross sections were extracted over the photon energy range 4.4– 5.4 GeV and binned in invariant momentum transfer t, providing measurements from one of the first high-statistics experiments of forward ¿ and ¿1 pro duction from a nuclear target at these energies. Acceptance corrections were applied using a detailed GEANT-based simulation of the detector geometry and response. The resulting cross sections are consistent with 2020 CLAS results, when scaled by the number of protons in beryllium, and show broad agreement with other data and theoretical models. In parallel, a high-resolution photon tagger detector, the Tagger Microscope (TAGM), was designed, constructed, and commissioned for the GlueX experiment in Hall D at Jefferson Lab. The TAGM was developed to provide high-rate tagging capability in the coherent bremsstrahlung peak by detecting post-bremsstrahlung electrons across a one GeV range along the focal plane of the tagging spectrometer. The detector consists of a 5ˆ102 array of 2ˆ2 mm2 square BCF-20 plastic scintillating fibers thermally fused to BCF-98 light guide fibers optically coupled to silicon photomultipliers. These fibers are mounted in a precision machined framework enabling fine positional adjustments to maintain precise alignment with post-bremsstrahlung electron trajectories, while ensuring mechanical rigidity, thermal stability, optical isolation, minimal inactive area, and radiation shielding for electronics. The construction effort involved extensive testing of fiber quality, light transmission, thermal fusing, radiation hardness, and defect analysis using SEM and EDX techniques. Following its installation and commissioning, the TAGM became a critical component of the GlueX beamline, enabling high-rate tagging essential for studies of hybrid mesons and gluonic ex citations.
McIntyre, James [Univ. of Connecticut, Storrs, CT ↗
Informing nuclear physics via machine learning methods with differential and integral experiments
Information from differential nuclear-physics experiments and theory is often too uncertain to accurately define nuclear-physics observables such as cross sections or energy spectra. Integral experimental data, representing the applications of these observables, are often more precise but depend simultaneously on too many of them to unambiguously identify issues in the observable with human expert analysis alone. Here, we explore how we can leverage physics knowledge gained from differential experimental data, nuclear theory, integral experiments, and neutron-transport calculations to better understand nuclear-physics observables in the context of the application area represented by integral experiments. We support this task with machine-learning methods to discern trends in a large amount of convoluted data. Differential and integral information was used in an analysis augmented by the random forest and the Shapley additive explanations metric. We chose as an application area one that is represented by criticality measurements and pulsed-sphere neutron-leakage spectra. We show one representative example ( 241 Pu fission observables) where the combination of differential and integral information allowed to resolve issues in data representing these observables. As a starting point, the machine learning (ML) algorithms highlighted several observables as leading potentially to bias in simulating integral experiments. Differential information, paired with sensitivity to integral quantities, allowed us then to pinpoint one specific observable ( 241 Pu fission cross section) as the main driver of bias. The comparison to integral experiments, on the other hand, allowed us to indicate a likely reliable experiment among several discrepant ones for this observables. In other cases (e.g., 239 Pu observables), we were not able to resolve the confounding introduced by integral experiments but instead highlighted the need for targeted new experiments and theory developments to better constrain the nuclear-physics space for the application area represented by integral experiments. We were able to combine information from differential experimental data, nuclear-physics theory, integral experiments, and neutron-transport simulations of the latter experiments with the help of the random forest algorithm and expert judgment. This combination of knowledge allows to improve our description of nuclear-physics observables as applied to a particular application area.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Drive-pressure optimization in ramp-wave compression experiments through differential evolution
Ramp-wave dynamic-compression experiments are used to examine quasi-isentropic loading paths in materials. The gradual and continuous increase in pressure created by ramp waves make these types of experiments ideal for studying nonequilibrium material behavior, such as solidification kinetics. In ramp-wave compression experiments, the input drive pressure to the experimental setup may be exerted through one of a number of different mechanisms (e.g., magnetic fields, gas-gun-driven impactors, or high-energy lasers) and is generally required for simulating such experiments. Yet, regardless of the specific mechanism, this drive pressure cannot be measured directly (measurements are generally taken at a location near the back of the experimental setup through a transparent window), leading to an inverse problem where one must determine the drive pressure at the front of the experimental setup (i.e., the input) that corresponds to the particle velocity (the output) measured near the back of the experimental setup. Furthermore, we solve this inverse problem using a heuristic optimization algorithm, known as differential evolution, coupled with a multiphysics, hydrodynamics code that simulates the compression of the experimental setup. By running many rounds of forward simulations of the experimental setup, our optimization process iteratively searches for a drive pressure that is optimized to closely reproduce the experimentally measured particle velocity near the back of the experimental setup. While our optimization methodology requires a significant number of hydrodynamics simulations to be conducted, many of these can be performed in parallel, which greatly reduces the time cost of our methodology. One novel aspect of our method for determining the drive pressure is that it does not require physical modeling of the drive mechanism and can thus be broadly applied to many types of ramp-compression experiments, regardless of the drive mechanism.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Year-around survey and manipulation experiments reveal differential sensitivities of soil prokaryotic and fungal communities to saltwater intrusion in Florida Everglades wetlands
Global sea-level rise is transforming coastal ecosystems, especially freshwater wetlands, in part due to increased episodic or chronic saltwater exposure, leading to shifts in biogeochemistry, plant- and microbial communities, as well as ecological services. Yet, it is still difficult to predict how soil microbial communities respond to the saltwater exposure because of poorly understood microbial sensitivity within complex wetland soil microbial communities, as well as the high spatial and temporal heterogeneity of wetland soils and saltwater exposure. To address this, we first conducted a two-year survey of microbial community structure and bottom water chemistry in submerged surface soils from 14 wetland sites across the Florida Everglades. We identified ecosystem-specific microbial biomarker taxa primarily associated with variation in salinity. Bacterial, archaeal and fungal community composition differed between freshwater, mangrove, and marine seagrass meadow sites, irrespective of soil type or season. Especially, methanogens, putative denitrifying methanotrophs and sulfate reducers shifted in relative abundance and/or composition between wetland types. Methanogens and putative denitrifying methanotrophs declined in relative abundance from freshwater to marine wetlands, whereas sulfate reducers showed the opposite trend. A four-year experimental simulation of salt-water intrusion in a pristine freshwater site and a previously saltwater-impacted site corroborated the highest sensitivity and relative increase of sulfate reducers, as well as taxon-specific sensitivity of methanogens, in response to continuously pulsing of saltwater treatment. Collectively, these results suggest that besides increased salinity, saltwater-mediated increased sulfate availability leads to displacement of methanogens by sulfate reducers even at low or temporal salt exposure. In conclusion, these changes of microbial composition could affect organic matter degradation pathways in coastal freshwater wetlands exposed to sea-level rise, with potential consequences, such as loss of stored soil organic carbon.
54 ENVIRONMENTAL SCIENCES↗
Modifications to the Theory of the Differential Absorption Experiment
Use of Fresnel reflection coefficient for studying reflections from mesosphere
MESOSPHERE↗
Differential Ranging Experiments with NASA’s High-Gain Deep Space Network Antennas
Radar experiments are currently under way at the Goldstone Deep Space Communications Complex (GDSCC) to determine the range of cis-lunar objects using a single high-gain 34m antenna transmitting 20 kW at X-band wavelengths, and two 34m receivers located at the GDSCC. The 34m antennas of the Deep Space Network (DSN) have effective fields-of-view of approximately 1 milli-radians, hence predetermined pointing predicts with accuracies on the order of 1 milli-degree are required. The extremely accurate 1 nano-second timing distribution of the DSN network enables sub-meter level ranging in the radial direction, by measuring delays in phase-modulated pseudonoise (PN) echoes reflected from the target. In this paper we demonstrate experimental verification of the proposed techniques by post-processing radar reflections obtained from a decommissioned geo-synchronous satellite. The characteristics of correlation-based delay measurements obtained simultaneously with two different receiving antennas are described. These are the fundamental quantities used to form the “time difference of arrival” (TDOA) observables commonly used in GPS positioning algorithms, and the results interpreted in the context of hyperbolic position location that could be used in the future to monitor spacecraft in cis-lunar space.
Cheung, Kar-Ming↗
Uncovering Where Compensating Errors Could Hide in ENDF/B-VIII.0
Unconstrained physics spaces between two or more nuclear data observables in a library occur when their values can be simultaneously adjusted without violating the uncertainties in either differential information or simulations of relevant integral experiments. Differential data are often too imprecise to fully bound all nuclear data observables of interest for application simulations. Integral data are simulated with combinations of nuclear data so that an error in one observable may be hidden by a counterbalancing error in another. In this manner compensating errors may lurk within nuclear data libraries and these errors have the potential to undermine the predictive power of neutron transport simulations, particularly in situations where there is no conclusive validation experiment that resembles the application of interest. The EUCLID project (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) developed a preliminary workflow to identify these unconstrained physics spaces by bringing together results from a large collection of integral experiments with their simulated counter-parts as well as differential information that have a one-to-one correspondence to nuclear data. This wealth of information is processed by machine learning tools for subsequent refinement by human experts. Here, we show how the EUCLID work-flow is executed by applying it first to 239 Pu and then to 9 Be nuclear data in ENDF/B-VIII.0.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Uncovering Where Compensating Errors Could Hide in ENDF/B-VIII.0
Unconstrained physics spaces between two or more nuclear data observables in a library occur when their values can be simultaneously adjusted without violating the uncertainties in either differential information or simulations of relevant integral experiments. Differential data are often too imprecise to fully bound all nuclear data observables of interest for application simulations. Integral data are simulated with combinations of nuclear data so that an error in one observable may be hidden by a counterbalancing error in another. In this manner compensating errors may lurk within nuclear data libraries and these errors have the potential to undermine the predictive power of neutron transport simulations, particularly in situations where there is no conclusive validation experiment that resembles the application of interest. The EUCLID project (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) developed a preliminary workflow to identify these unconstrained physics spaces by bringing together results from a large collection of integral experiments with their simulated counter-parts as well as differential information that have a one-to-one correspondence to nuclear data. This wealth of information is processed by machine learning tools for subsequent refinement by human experts. Here, we show how the EUCLID work-flow is executed by applying it first to 239 Pu and then to 9 Be nuclear data in ENDF/B-VIII.0.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NCSP Nuclear Data Program [Slides]
This talk covers wide-ranging information on the Nuclear Criticality Safety Program (NCSP) Data Program. The Lecture includes slides on the history and mission of the NCSP along with charts and graphs on budgets from 2005 onwards. This lecture additionally mentions NCSP critical assemblies, differential experiments, and data measurements and evaluation work. The talk concludes with a gaze into NCSP benefits and successes.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
INDEN Fissile Actinide Issues [Slides]
This presentation addresses the outlook for the International Nuclear Data Evaluation Network (INDEN), specifically regarding general issues that have been solved, including Thermal Neutron Constants (TNC) and Prompt Fission Neutron Spectra (PFNS). Other topics discussed include outstanding issues in fissile evaluations, comments on the RPI quasi-differential experiment, and reaction rate testing of trial evaluations in fast assemblies. The presentation concludes by discussing how INDEN interactions strongly helped to find deficiencies in existing evaluations and highlighted potential solutions to existing challenges, that updated trial evaluations for U-235, U-233, Pu-239 are available for testing, that further work is expected on U-235, Pu-239, and U-233, and that performance was tested on the ICSBEP and/or SINBAD benchmarks, during which significant improvement was demonstrated. The INDEN scheme of international collaboration on nuclear data evaluation is working well.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Fast neutron leakage spectra of the EUCLID experiment
Special nuclear material in sub-critical and critical configurations measured in integral experiments are important for validation and adjustment of nuclear data. Many different evaluations of nuclear data exist, and these different evaluations can provide different values for individual cross sections that vary due to the uncertainties in differential experiments or lack of such data. For integral experiments, differences in these individual cross sections can have compensating errors, which lead to the same answer. One example of this is the Jezebel critical assembly, where k eff of the system is correctly computed by both ENDF/B-VIII.0 and JEFF-3.3, despite having substantially different underlying evaluated values for specific reactions (such as elastic and inelastic cross sections). To reduce compensating errors in nuclear data, the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project has utilized machine learning to design a set of sub-critical and critical experiments. These experiments include slab- and cube-like configurations of 239 Pu in the form of the ZPPR plates. Six different responses were measured on a total of thirteen different configurations. One of these responses, the neutron leakage spectrum, was measured using an EJ301D detector. Finally, the results of the neutron leakage spectra show good agreement (within 1–2 σ ) with the expected spectrum from simulations and will be used in the subsequent nuclear data adjustment done by the EUCLID team.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
181 Ta - fast neutron evaluation [Slides]
Reliable fast-neutron evaluation can be entirely encapsulated in the reaction model and related input. Ta181 is a particularly relevant case due to extraordinary coverage of various observables by differential experiments that offer much help and relatively little headache. Differences from the similar ENDF/B-VIII evaluation include: more advanced modeling (CC OMP, MSD, MSC, decay schemes), more careful selection of models and parameters, new experimental data, and isomers. Overall, improved agreement with differential data and hints of better performance in integral testing.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Neutron Leakage Spectra of the EUCLID Experiment [Abstract]
Integral experiments with sub-critical and critical configurations of special nuclear material are performed in support of nuclear data validation and adjustment. Different nuclear data evaluations may have different values for individual cross sections due to uncertainties in (or lack of) differential experiments, but compensating errors in these data sets can lead to the same k eff results for one application while vastly different for another application. One example of this is 239 Pu, where both ENDF/B-VIII.0 and JEFF-3.3 correctly compute k eff of the Jezebel critical assembly, but the individual contributions from each reaction are vastly different. To help resolve this specific case, the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project used machine learning to design a set of experiments to help resolve the compensating errors in 239 Pu. A total of six responses were measured during the experimental campaign, which constrain the data in ways that k eff alone cannot and will be used for adjustment of the nuclear data. One of these responses is the neutron leakage spectrum, which recent work has shown to be useful for constraining the prompt fission neutron spectrum and inelastic scattering. The neutron leakage spectra were measured utilizing a 3 in. right cylinder EJ-301D detector. The measured signal in the detector was deconvoluted using spectrum unfolding techniques, which are presented and compared to simulations.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Update on 17 O evaluation and fast neutron evaluation for 181 Ta [Slides]
Reliable fast-neutron evaluation can be entirely encapsulated in the reaction model and related input. Ta181 is a particularly relevant case due to extraordinary coverage of various observables by differential experiments that offer much help and relatively little headache. Differences from the similar ENDF/B-VIII evaluation are as follows: more advanced modeling (CC OMP, MSD, MSC, decay schemes), more careful selection of models and parameters, new experimental data, and isomers. Overall, there is improved agreement with differential data and hints of better performance in integral testing.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗