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DOE OSTI2024

Visibility-enhanced model-free deep reinforcement learning algorithm for voltage control in realistic distribution systems using smart inverters

Increasing integration of distributed solar photovoltaic (PV) into distribution networks could result in adverse effects on grid operation. Traditional model-based control algorithms require accurate model information that is difficult to acquire and thus are challenging to implement in practice. Here, this paper proposes a surrogate model-enabled grid visibility scheme to empower deep reinforcement learning (DRL) approach for distribution network voltage regulation using PV inverters with minimal system knowledge. In contrast to existing DRL methods, this paper presents and corroborates the adverse impact of missing load information on DRL performance and, based on this finding, proposes a surrogate model methodology to impute load information utilizing observable data. Additionally, a multi-fidelity neural network is utilized to construct the DRL training environment, chosen for its efficient data utilization and enhanced robustness to data uncertainty. The feasibility and effectiveness of the proposed algorithm are assessed by considering DRL testing across varying degrees of observable load information and diverse training environments on a realistic power system.

14 SOLAR ENERGY↗

NASA NTRS1975

Wavefront-error evaluation by mathematical analysis of experimental Foucault-test data

The diffraction theory of the Foucault test provides an integral formula expressing the complex amplitude and irradiance distribution in the Foucault pattern of a test mirror (lens) as a function of wavefront error. Recent literature presents methods of inverting this formula to express wavefront error in terms of irradiance in the Foucault pattern. The present paper describes a study in which the inversion formulation was applied to photometric Foucault-test measurements on a nearly diffraction-limited mirror to determine wavefront errors for direct comparison with ones determined from scatter-plate interferometer measurements. The results affirm the practicability of the Foucault test for quantitative wavefront analysis of very small errors, and they reveal the fallacy of the prevalent belief that the test is limited to qualitative use only. Implications of the results with regard to optical testing and the potential use of the Foucault test for wavefront analysis in orbital space telescopes are discussed.

Wilson, R. G.↗

NASA NTRS2005

Characteristics Of Ferroelectric Logic Gates Using a Spice-Based Model

A SPICE-based model of an n-channel ferroelectric field effect transistor has been developed based on both theoretical and empirical data. This model was used to generate the I-V characteristic of several logic gates. The use of ferroelectric field effect transistors in memory circuits is being developed by several organizations. The use of FFETs in other circuits, both analog and digital needs to be better understood. The ability of FFETs to have different characteristics depending on the initial polarization can be used to create logic gates. These gates can have properties not available to standard CMOS logic gates, such as memory, reconfigurability and memory. This paper investigates basic properties of FFET logic gates. It models FFET inverter, NAND gate and multi-input NAND gate. The I-V characteristics of the gates are presented as well as transfer characteristics and timing. The model used is a SPICE-based model developed from empirical data from actual Ferroelectric transistors. It simulates all major characteristics of the ferroelectric transistor, including polarization, hysteresis and decay. Contrasts are made of the differences between FFET logic gates and CMOS logic gates. FFET parameters are varied to show the effect on the overall gate. A recodigurable gate is investigated which is not possible with CMOS circuits. The paper concludes that FFETs can be used in logic gates and have several advantages over standard CMOS gates.

MacLeod, Todd C.↗

DOE OSTI2016

Optimal Power Flow Pursuit

Past works that focused on addressing power-quality and reliability concerns related to renewable energy resources (RESs) operating with business-as-usual practices have looked at the design of Volt/VAr and Volt/Watt strategies to regulate real or reactive powers based on local voltage measurements, so that terminal voltages are within acceptable levels. These control strategies have the potential of operating at the same time scale of distribution-system dynamics, and can therefore mitigate disturbances precipitated fast time-varying loads and ambient conditions; however, they do not necessarily guarantee system-level optimality, and stability claims are mainly based on empirical evidences. On a different time scale, centralized and distributed optimal power flow (OPF) algorithms have been proposed to compute optimal steady-state inverter setpoints, so that power losses and voltage deviations are minimized and economic benefits to end-users providing ancillary services are maximized. However, traditional OPF schemes may offer decision making capabilities that do not match the dynamics of distribution systems. Particularly, during the time required to collect data from all the nodes of the network (e.g., loads), solve the OPF, and subsequently dispatch setpoints, the underlying load, ambient, and network conditions may have already changed; in this case, the DER output powers would be consistently regulated around outdated setpoints, leading to suboptimal system operation and violation of relevant electrical limits. The present work focuses on the synthesis of distributed RES-inverter controllers that leverage the opportunities for fast feedback offered by power-electronics interfaced RESs. The overarching objective is to bridge the temporal gap between long-term system optimization and real-time control, to enable seamless RES integration in large scale with stability and efficiency guarantees, while congruently pursuing system-level optimization objectives. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. The proposed controllers enable an update of the power outputs at a time scale that is compatible with the underlying dynamics of loads and ambient conditions, and continuously drive the system operation towards OPF-based solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2000

Estimates of Ground Temperature and Atmospheric Moisture from CERES Observations

A method is developed to retrieve surface ground temperature (T(sub g)) and atmospheric moisture using clear sky fluxes (CSF) from CERES-TRMM observations. In general, the clear sky outgoing longwave radiation (CLR) is sensitive to upper level moisture (q(sub l)) over wet regions and (T(sub g)) over dry regions The clear sky window flux from 800 to 1200/cm (RadWn) is sensitive to low level moisture (q(sub t)) and T(sub g). Combining these two measurements (CLR and RadWn), Tg and q(sub h) can be estimated over land, while q(sub h) and q(sub l) can be estimated over the oceans. The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic CSF data from two different global 4-dimensional data assimilation products. Simple linear regression is used to relate discrepancies in CSF to discrepancies in T(sub g), q(sub h) and q(sub l). The slopes of the regression lines define sensitivity parameters that can be exploited to help interpret mismatches between satellite observations and model-based estimates of CSF. For illustration, we analyze the discrepancies in the CSF between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS-DAS) and a recent operational version of the European Center for Medium-Range Weather Prediction data assimilation system. In particular, our analysis of synthetic total and window region SCF differences (computed from two different assimilated data sets) shows that simple linear regression employing Delta(T(sub g)) and broad layer Delta(q(sub l) from .500 hPa to surface and Delta(q(sub h)) from 200 to .300 hPa provides a good approximation to the full radiative transfer calculations. typically explaining more than 90% of the 6-hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the geophysical parameters. Uncertainties (normalized by standard deviation) in the monthly mean retrieved parameters range from 7% for Delta(T(sub g)) to about 20% for Delta(q(sub l)). Our initial application of the methodology employed an early CERES-TRMM data set (CLR and Radwn) to assess the quality of the GEOS2 data. The results showed that over the tropical and subtropical oceans GEOS2 is, in general, too wet in the upper troposphere (mean bias of 0.99 mm) and too dry in the lower troposphere (mean bias of -4.7 min). We note that these errors, as well as a cold bias in the T(sub g). have largely been corrected in the current version of GEOS-2 with the introduction of a land surface model, a moist turbulence scheme and the assimilation of SSM/I total precipitable water.

Wu, Man Li C.↗

DOE OSTI2018

Quadri-joint inversion: Method and application to the Big Sky 9C 3D data set in northern Montana

The Kevin Dome [Formula: see text] storage project, located in northern Montana, attempted to characterize the Duperow Formation as a potential long-term storage zone for injected [Formula: see text]. A multicomponent (9C) seismic survey was acquired for the Big Sky Carbon Sequestration Partnership over a portion of the Kevin Dome using P- and S-wave sources. Prestack migrated PP, PS, SH, and SV data sets were generated. We then applied several stratigraphic inversion workflows using one or several kinds of seismic wavefield at the same time resulting in joint inversions of each data set. The aim of our study is to demonstrate the benefits of doing quadri-joint inversion of PP-, PS-, SH-, and SV-wavefields for the recovery of the elastic earth parameters, especially the S-wave impedance and density. These are crucial parameters because they can help determine lithology and porefill in the reservoir characterization workflow. Because the inversion workflow always uses the original seismic data recorded in its own time domain, it is necessary to compute registration laws between PP-PS-, PP-SH-, and PP-SV-wavefields using a time shift computation procedure (warping) based on inverted S-wave impedances from inversion of a single wavefield. This generated a significant improvement over methods that rely on attempting to match trace waveforms that may have a different phase, frequency content, and polarity. Finally, we wanted to investigate the reliability of the quadri-joint inversion results in the Bakken/Banff Formations, which have less lateral geologic variation than the underlying Duperow target. This interval shares many of the geophysical characterization challenges common to shale reservoirs in other North American basins. We computed geomechanical parameters, such as Poisson’s ratio and Young’s modulus, which are a proxy for brittleness. Comparison of these results with independent laboratory measurements in the Bakken interval demonstrates the superiority of the quadri-joint inversion method to the traditional inversion using P-wave data only.

Geochemistry & Geophysics↗

DOE OSTI2017

Box tomography: localized imaging of remote targets buried in an unknown medium, a step forward for understanding key structures in the deep Earth

We discuss an application of tomographic methods to the imaging of localized geological structures buried inside the Earth, where neither seismic sources nor receivers are necessarily present. We call this ‘box tomography’. The essential difference between box-tomography and standard tomographic methods is that the numerical modelling (i.e. the ray tracing in traveltime tomography and the wave propagation in waveform tomography or full waveform inversion) is completely confined within the small box-region imaged. Thus, box tomography is a lot more efficient than global tomography (i.e. where we invert for the velocity in the larger volume that encompasses all the sources and receivers), for imaging localized objects. The principal difficulty in the box tomography problem comes from the medium outside the box-region imaged, that masks the target structure. In the data recorded at the surface, the information carried by the waves about the target structure is mixed with that about the surrounding medium. The main focus of this paper is to evaluate how well box tomography can extract useful information to produce accurate images of remote buried objects, especially in the difficult situation where the velocity distribution above the target structure is not known a priori. We implemented traveltime box tomography, where first arrival times are inverted using ray theory, and, waveform box tomography or full waveform box inversion, where seismograms are inverted using either scattering integrals or adjoint methods. Whatever the method employed, we found that, in the simple situation where the velocity structure is known around the target region, box-tomography is faster and more accurate than global tomography. Most importantly, through examples and simple analysis, we show that box-tomography can produce accurate images of localized structures even though the velocity distribution is not a priori known around the box-region imaged. In the last section of this paper, we evaluate the usage of box-tomography for imaging geological structures in the deep Earth. We performed 2-D synthetic experiments in a fluid planet and we argue that box tomography can be employed for refining our current global tomographic models within arbitrary regions inside the Earth. This has important implications for understanding the composition and dynamics of the Earth’s interior.

Masson, Yder↗

DOE OSTI2023

Heterogeneity or illusion? Track the carbon Kuznets curve of global residential building operations

Residential buildings, the “last mile” sector in the global decarbonization, have become the most significant uncertain factor hindering carbon neutrality with increasing household energy demand. To track the operational carbon in buildings, this study investigates the carbon Kuznets curve (CKC) and the corresponding decoupling status of residential building operations at four emission scales by using the data of 30 countries from 2000 to 2019. The results show that (1) the CKC model can fit more than half of the samples. Most curves have an inverted U-shape, with 76% of emission per household and 82% of total emissions. (2) In the presence of the CKC, over four-fifths of global residential buildings peak regardless of any emission scale. The analysis denotes that the carbon emissions of developed countries reach their peaks earlier. In the total emissions, the samples’ peaking proportion is 20% and 25% with income per capita < 20,000 United States dollars (USD) and 20,000–40,000 USD, respectively. (3) The Tapio decoupling analysis and the threshold regression effectively verify the robustness and the heterogeneity of CKCs, respectively. Strong decoupling effects of CKCs in most countries are demonstrated at the scales of emission per floor space and the total emissions, and the heterogeneity proves the classic inverted U-shaped relationship between economy and emissions doesn’t exist in all emitters. Overall, this study tracks the historical carbon emission trajectories of residential building operations at a global scale, providing reference for different economies to simulate the dynamic of building carbon emissions along with the economic booming.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2011

A field-reversed magnetic configuration and applications of high-temperature FRC plasma

As applied to a tokomak, a magnetic trap for confinement of a plasma with an inverted field or a magnetic field reversed configuration (FRC) is one of the most promising alternatives of the systems with high {beta}. A brief review of the latest data on FRC and potential directions of using such configurations in addition to energy generation in thermonuclear reactors (TNRs) is proposed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1982

Single event upset vulnerability of selected 4K and 16K CMOS static RAM's

Upset thresholds for bulk CMOS and CMOS/SOS RAMS were deduced after bombardment of the devices with 140 MeV Kr, 160 MeV Ar, and 33 MeV O beams in a cyclotron. The trials were performed to test prototype devices intended for space applications, to relate feature size to the critical upset charge, and to check the validity of computer simulation models. The tests were run on 4 and 1 K memory cells with 6 transistors, in either hardened or unhardened configurations. The upset cross sections were calculated to determine the critical charge for upset from the soft errors observed in the irradiated cells. Computer simulations of the critical charge were found to deviate from the experimentally observed variation of the critical charge as the square of the feature size. Modeled values of series resistors decoupling the inverter pairs of memory cells showed that above some minimum resistance value a small increase in resistance produces a large increase in the critical charge, which the experimental data showed to be of questionable validity unless the value is made dependent on the maximum allowed read-write time.

Kolasinski, W. A.↗

NASA NTRS1985

Binning of satellite magnetic anomalies

Crustal magnetic anomaly signals over satellite orbits were simulated to investigate numerical averaging as an anomaly estimator. Averaging as an anomaly estimator involves significant problems concerning spatial and amplitude smoothing of the satellite magnetic observations. The results of simulations suggest that the error of numerical averaging constitutes a small and relatively minor component of the total error-budget of higher orbital anomaly estimates, whereas for lower orbital estimates numerical averaging error increases substantially. As an alternative to numerical averaging, least-squares collocation was investigated and observed to produce substantially more accurate anomaly estimates, particularly as the orbital elevation of prediction was decreased towards the crustal sources. In contrast to averaging, collocation is a significantly more resource-intensive procedure to apply because of the practical, but surmountable problems related to establishing and inverting the covariance matrix for accurate anomaly prediction. However, collocation may be much more effectively used to exploit the anomaly details contained in the lower orbital satellite magnetic data for geologic analysis.

Goyal, H. K.↗

NASA NTRS1994

Hydrogen and related materials at high density: Physics, chemistry and planetary implications

Recent studies of low-Z molecular materials including hydrogen to multimegabar pressures (less than 300 GPa) have uncovered a range of phenomena relevant to understanding the nature of the interiors of the outer planets and their satellites. Synchrotron x ray diffraction measurements (to 42 GPa) have been used to determine the crystal structure of the solid (hexagonal-close packed) and equation of state. Sound velocities in fluid and solid hydrogen (to 24 GPa) have been inverted to obtain elastic constants and aggregate bulk and shear moduli. In addition, an improved intermolecular potential has been determined which fits both static and shock-wave data. Use of the new potential for the molecular envelope of Jupiter suggests the need for major revisions of existing Jovian models or a reanalysis of reported free oscillations for the planet. Studies at higher pressures (greater than 100 GPa) reveal a sequence of pressure-induced symmetry-breaking transitions in molecular hydrogen, giving rise to three high-pressure phases (1, 2, and 3). Phase 1 is the rotationally disordered hcp phase which persists from low pressure to well above 100 GPa at high temperature (e.g., 300 K). Phase 2 is a low-temperature, high-pressure phase (transition at 100 GPa and 77 K in H2) with spectral features indicative of partial rotational ordering and crystallographic distortion. The transition to Phase 3 at 150 GPa is accompanied by a weakening of the molecular bond, gradual changes in orientational ordering, strong enhancement of the infrared intramolecular vibrational absorption, and strong intermolecular interactions similar to those of ambient-pressure network solids. Studies of the phase diagram reveal a triple point near 130 K and 160 GPa. Higher pressure measurements of vibrational spectra place a lower bound of approximately 250 GPa on the predicted transition pressure for dissociation of molecular hydrogen to form a monatomic metal.

Hemley, R. J.↗

NASA NTRS2011

Time-Distance Helioseismology Data-Analysis Pipeline for Helioseismic and Magnetic Imager Onboard Solar Dynamics Observatory (SDO-HMI) and Its Initial Results

The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) provides continuous full-disk observations of solar oscillations. We develop a data-analysis pipeline based on the time-distance helioseismology method to measure acoustic travel times using HMI Doppler-shift observations, and infer solar interior properties by inverting these measurements. The pipeline is used for routine production of near-real-time full-disk maps of subsurface wave-speed perturbations and horizontal flow velocities for depths ranging from 0 to 20 Mm, every eight hours. In addition, Carrington synoptic maps for the subsurface properties are made from these full-disk maps. The pipeline can also be used for selected target areas and time periods. We explain details of the pipeline organization and procedures, including processing of the HMI Doppler observations, measurements of the travel times, inversions, and constructions of the full-disk and synoptic maps. Some initial results from the pipeline, including full-disk flow maps, sunspot subsurface flow fields, and the interior rotation and meridional flow speeds, are presented.

Sun: helioseismology↗

DOE OSTI2019

“Inverting” X-ray Absorption Spectra of Catalysts by Machine Learning in Search for Activity Descriptors

The rapid growth of methods emerging in the past decade for synthesis of “designer” catalysts—ranging from the size and shape-selected nanoparticles to mass-selected clusters, to precisely engineered bimetallic surfaces, to single site and pair site catalysts—has opened opportunities for tailoring the catalyst structure for the desired activity and selectivity. It has also sharpened the need for developing approaches to the operando characterization, ones that identify the catalytic active sites and follow their evolutions in reaction conditions. Commonly used methods for determination of the activity descriptors in the nanocatalysts, based on the correlation between the changes in catalyst performance and evolution of its structural and electronic properties, are hampered by the paucity of experimental techniques that can detect such properties with high accuracy and in reaction conditions. Out of many such techniques, X-ray absorption spectroscopy (XAS) stands out as an element-specific method that is very sensitive to the local geometric and electronic properties of the metal atoms and their surroundings and, therefore, is able to track catalyst structure modifications in operando conditions. Despite the vast amount of structure-specific information (such as, e.g., the charge states and radial distribution function of neighbors of selected atomic species) stored in the XAS data of catalysts, extracting it from the spectra is challenging, especially in the conditions of low metal weight loading, nanoscale dimensions, heterogeneous size and composition distributions, and harsh reaction environment. In this Perspective, we discuss the recent developments in XAS data analysis achieved by employing supervised and unsupervised machine learning (ML) methods for structural characterization of catalysts. By benefiting from the sensitivity of ML methods to subtle variations in experimental data, a previously “hidden” relationship between the X-ray absorption spectrum and descriptors of material’s structure and/or composition can be found, as illustrated on representative examples of mono-, hetero-, and nonmetallic catalysts. In the case of supervised ML, the experimental spectra can be rapidly “inverted”, and the structure of the catalyst can be tracked in real time and in reaction conditions. Finally, emerging opportunities for catalysis research that the ML methods enable, such as high-throughput data analysis, and their applications to other experimental probes of catalyst structure are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Experimental Test Bed to Enable Realistic Evaluations for Direct Transfer Trip Relaying via Private Wireless LTE Communications: Preprint

Increasing penetration levels of inverter-based distributed energy resources (DERs) in distribution systems are creating challenges in system operation. Currently, wired or proprietary wireless communications are used by advanced distribution management systems (ADMS) to detect the state of the system and control the DERs for optimal operation. Wireless communications are an alternative solution that can enable connectivity between the dispersed assets used in distribution system applications. This paper demonstrates an experimental test bed to enable the realistic evaluation of communications system characteristics for direct transfer trip (DTT) relaying of a photovoltaic inverter system using a private 900-MHz spectrum wireless LTE network. Private LTE network communications can be deployed to many remote DERs and other grid-edge devices to prevent costly infrastructure upgrades across distribution systems. In addition, this paper provides a framework for evaluating the impact of signal strength and network traffic in communications systems. The results shown develop a better understanding of the best practices for using LTE communications systems across multiple utility applications, such as protective relaying, voltage regulation, and supervisory control and data acquisition system messages.

900 MHz LTE network↗

DOE OSTI2016

Intermediate-Scale Hydraulic Fracturing in a Deep Mine - kISMET Project Summary 2016

In support of the U.S. DOE SubTER Crosscut initiative, we established a field test facility in a deep mine and designed and carried out in situ hydraulic fracturing experiments in the crystalline rock at the site to characterize the stress field, understand the effects of rock fabric on fracturing, and gain experience in monitoring using geophysical methods. The project also included pre- and post-fracturing simulation and analysis, laboratory measurements and experiments, and we conducted an extended analysis of the local stress state using previously collected data. Some of these activities are still ongoing. The kISMET (permeability (k) and Induced Seismicity Management for Energy Technologies) experiments meet objectives in SubTER’s “stress” pillar and the “new subsurface signals” pillar. The kISMET site was established in the West Access Drift of SURF 4850 ft (1478 m) below ground (on the 4850L) in phyllite of the Precambrian Poorman Formation. We drilled and cored five near-vertical boreholes in a line on 3 m spacing, deviating the two outermost boreholes slightly to create a five-spot pattern around the test borehole centered in the test volume at ~1528 m (5013 ft). Laboratory measurements of core from the center test borehole showed P-wave velocity heterogeneity along each core indicating strong, fine-scale (~1 cm or smaller) changes in the mechanical properties of the rock. The load-displacement record on the core suggests that the elastic stiffness is anisotropic. Tensile strength ranges between 3-7.5 MPa and 5-12 MPa. Permeability measurements are planned, as are two types of laboratory miniature hydraulic fracturing experiments to investigate the importance of rock fabric (anisotropy and heterogeneity) on near-borehole hydraulic fracture generation. Pre-fracturing numerical simulations with INL’s FALCON discrete element code predicted a fracture radius of 1.2 m for a corresponding injection volume of 1.2 L for the planned fractures, and negligible microseismicity. Field measurements of the stress field by hydraulic fracturing showed that the minimum horizontal stress at the kISMET site averages 21.7 MPa (3146 psi) pointing approximately N-S (356 degrees azimuth) and plunging slightly NNW at 12°. The vertical and horizontal maximum stress are similar in magnitude at 42-44 MPa (6090-6380 psi) for the depths of testing which averaged approximately 1530 m (5030 ft). Hydraulic fractures were remarkably uniform suggesting core-scale and larger rock fabric did not play a role in controlling fracture orientation. Monitoring using ERT and CASSM in the four monitoring boreholes, and passive seismic accelerometer-based measurements in the West Access Drift, was carried out during the generation of a larger fracture (so-called stimulation test) at a depth of 40 m below the invert. ERT was not able to detect the fracture created, nor were the accelerometers in the drift, but microseismicity was detected for first (deepest) hydraulic-fracturing stress measurement. The CASSM data have not yet been analyzed. Analytical solutions suggest fracture radius of the large fracture (stimulation test) was more than 6 m, depending on the unknown amount of leak-off. The kISMET results for stress state are consistent with large-scale mid-continent estimates of stress. Currently we are using the orientation of the stress field we determined to interpret a large number of borehole breakouts recorded in nearby boreholes at SURF to generate a more complete picture of the stress field and its variations at SURF. The efforts on the project have prompted a host of additional follow-on studies that we recommend be carried out at the kISMET site.

02 PETROLEUM↗

NASA NTRS2005

A Tower-based Prototype VHF/UHF Radar for Subsurface Sensing: System Description and Data Inversion Results

Knowledge of subsurface characteristics such as permittivity variations and layering structure could provide a breakthrough in many terrestrial and planetary science disciplines. For Earth science, knowledge of subsurface and subcanopy soil moisture layers can enable the estimation of vertical flow in the soil column linking surface hydrologic processes with that in the subsurface. For planetary science, determining the existence of subsurface water and ice is regarded as one of the most critical information needs for the study of the origins of the solar system. The subsurface in general can be described as several near-parallel layers with rough interfaces. Each homogenous rough layer can be defined by its average thickness, permittivity, and rms interface roughness assuming a known surface spectral distribution. As the number and depth of layers increase, the number of measurements needed to invert for the layer unknowns also increases, and deeper penetration capability would be required. To nondestructively calculate the characteristics of the rough layers, a multifrequency polarimetric radar backscattering approach can be used. One such system is that we have developed for data prototyping of the Microwave Observatory of Subcanopy and Subsurface (MOSS) mission concept. A tower-mounted radar makes backscattering measurements at VHF, UHF, and L-band frequencies. The radar is a pulsed CW system, which uses the same wideband antenna to transmit and receive the signals at all three frequencies. To focus the beam at various incidence angles within the beamwidth of the antenna, the tower is moved vertically and measurements made at each position. The signals are coherently summed to achieve focusing and image formation in the subsurface. This requires an estimate of wave velocity profiles. To solve the inverse scattering problem for subsurface velocity profile simultaneously with radar focusing, we use an iterative technique based on a forward numerical solution of the layered rough surface problem. The layers are each defined in terms of a small number of unknown distributions as given above. An a priori estimate of the solution is first assumed, based on which the forward problem is solved for the backscattered measurements. This is compared with the measured data and using iterative techniques an update to the solution for the unknowns is calculated. The process continues until convergence is achieved. Numerical results will be shown using actual radar data acquired with the MOSS tower radar system in Arizona in Fall 2003, and compared with in-situ measurements.

Moghaddam, Mahta↗

DOE OSTI2015

Estudo da Oscilação de Neutrinos Muônicos Usando Dados Atmosféricos e de Acelerador nos Experimentos MINOS e MINOS+

The MINOS (Main Injector Neutrino Oscillation Search) and MINOS+ experiments were designed to study neutrino oscillations using a muon neutrino beam which is detected in two different locations, in the Near Detector and in the Far Detector. The distance between the detectors allows the beam neutrinos to oscillate to a different flavor. Therefore, a disappearance of the muon neutrinos from the beam is observed in the Far Detector. The Far Detector has a special apparatus which makes possible the selection of atmospheric neutrinos and antineutrinos. These come from interactions of cosmic rays with the Earth’s atmosphere. Both detectors have a magnetic field, allowing the distiction between neutrinos and antineutrinos interactions. This thesis presents the first combined analysis of data from the MINOS and MINOS+ experiments. We have analyzed the combined neutrino energy spectrum from the complete MINOS beam data and the first, more energetic, MINOS+ beam data. The disappearance of the muon neutrinos was observed and the data has shown to be congruent with the oscillation model. Beyond that, we have measured the atmospheric oscillation parameters of the beam and atmospheric neutrinos and antineutrinos from MINOS combined with the atmospheric neutrinos and antineutrinos from MINOS+. Assuming the same oscillation parameters for both neutrinos and antineutrinos, the best fit is obtained for inverted hierarchy and lower octant with Δm 2 32 = 2:37 X 10 -3 eV 2 and sin 2 θ 23 = 0:43, and the limits m 2 32 = [2,29 - 2,49] 10 -3 eV 2 (68%) and sin 2 θ 23 = 0.36 - 0.66 (90%). These results are the most precise measurement of the neutrinos mass splitting using muon neutrino disappearance data only.

43 PARTICLE ACCELERATORS↗