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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

MO-C-9A-01: Effective Medical Physics Educational Activities: Models and Methods

Medical physics is learned in a combination of activities including classroom sessions, individual study, small-group collaborative problem solving, and direct experience in the laboratory or clinical environment. Each type of learning activity is characterized by its effectiveness in producing the desired knowledge for the learner and the cost in terms of resources and human effort required providing it. While learning and teaching is a human activity, modern technology provides a variety of tools that can be used to enhance human performance. The class or conference room is the common setting for educational sessions in both academic institutions and continuing education conferences and programs such as those sponsored by the AAPM. A major value of a class/conference room program is efficiency by bringing a group of learners together to share in a common learning experience under the guidance of one or more experienced learning facilitators (lecturers or presenters). A major challenge is that the class/conference room is separated from the real world of medical physics. The design of an educational activity needs to take into consideration the desired outcomes with respect to what the learners should be able to do. The distinction is that of being able to apply the knowledge to perform specific physics functions rather than just knowing and being able to recall facts, and perhaps do well on written examinations. These are different types of knowledge structures within the human brain and distinctly different learning activities to develop each. Much of medical physics education, especially at the post-graduate and continuing education level, is for the purpose of enhancing the ability of physicists and other related professionals to perform applied procedures and tasks and requires specific types of knowledge.In this session we will analyze various learning activity models, the values and limitations of each, and how they can be used in medical physics education. An example we will use is optimizing CT image quality and dose which is an important topic for medical physicists, radiologists and residents, along with technologists. The knowledge structure for this is best developed by a combination of learning activities including class/conference discussions, individual study and review, and direct observation and interaction in the clinical setting under the direction of a knowledgeable leader.The function of the human brain will be considered with respect to learning experiences that contribute to effective medical physics knowledge structures. The characteristics of various types of educational activities will be compared with respect to their effectiveness for producing desired outcomes along with their limitations. Emphasis will be given to the design of highly-effective classroom/conference presentations, and activities will be demonstrated with an emphasis on using technology to enhance human performance of both learners and the learning facilitators. Learning Objectives: Develop and provide highly effective medical physics educational sessions. Use technology to enhance human performance in the educational process. Identify and analyze various models of educational activities Select and use educational activities that contribute value to the medical physics profession.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1998

A Technique for Assimilating GOES-Derived Land Surface Products into Regional Models to Improve the Representation of Land Surface Forcing

As the parameterizations of surface energy budgets in regional models have become more complete physically, models have the potential to be much more realistic in simulations of coupling between surface radiation, hydrology, and surface energy transfer. Realizing the importance of properly specifying the surface energy budget, many institutions are using land-surface models to represent the lower boundary forcing associated with biophysical processes and soil hydrology. However, the added degrees of freedom due to inclusion of such land-surface schemes require the specification of additional parameters within the model system such as vegetative resistances, green vegetation fraction, leaf area index, soil physical and hydraulic characteristics, stream flow, runoff, and the vertical distribution of soil moisture. A technique has been developed for assimilating GOES-IR skin temperature tendencies into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. An advantage of this technique for short-range forecasts is that it does not require a complex land-surface formulation within the atmospheric model. As a result, the need to specify poorly known soil and vegetative characteristics is eliminated. The GOES assimilation technique has been incorporated into the PSU/NCAR MM5. Results will be presented to demonstrate the ability of the assimilation scheme to improve short-term simulations of near-surface air temperature and mixing ratio during the warm season for several selected cases during June of 1995 and June 1997 which exhibit a variety of atmospheric and land-surface conditions. In addition, the simulations produced by the assimilation technique will be compared with those produced by the MM5/BATS coupled model initialized with soil water content derived from a soil hydrology model.

Lapenta, William M.↗
NASA NTRS1999

Real-Time Assimilation of Goes-Derived Products into A Mesoscale Model and It's Impact on Short-Term (06-36hr) Forecasts from 17 October 1998 through the Present

As the parameterizations of surface energy budgets in regional models have become more complete physically, models have the potential to be much more realistic in simulations of coupling between surface radiation, hydrology, and surface energy transfer. Realizing the importance of properly specifying the surface energy budget, many institutions are using land-surface models to represent the lower boundary forcing associated with biophysical processes and soil hydrology. However, the added degrees of freedom due to inclusion of such land-surface schemes require the specification of additional parameters within the model system such as vegetative resistances, green vegetation fraction, leaf area index, soil physical and hydraulic characteristics, stream flow, runoff, and the vertical distribution of soil moisture. Spatial heterogeneity of these parameters makes correct specification problematic since measurements are not routinely available. A technique has been developed for assimilating GOES-IR skin temperature tendencies, solar insolation, and surface albedo into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. The technique has been successfully employed in a number of mesoscale models in case-study mode. We have taken the next step and developed a study to determine if assimilating these types of data into mesoscale models in real-time can improve short-term (648h) forecasts of temperature, relative humidity, and QPF on a daily basis over relatively large regions. Therefore, an operational modeling/assimilation system has been developed at the GHCC during the past summer that allows us to produce simulations out to 48 hours in a timely manor. The PSU/NCAR MM5 is used in a nested configuration with a 25 km grid covering the southeastern third of the US. The model has been on-line since 1 July 1998 and forecast products are posted on our web site. The satellite algorithms that generate data to be assimilated came on-line 17 October 1998. Quantitative assessment of the forecast quality is performed via traditional verification statistics. In addition, invaluable qualitative information is obtained through close collaboration with several NWSFO's who are using the MM5 products in real-time on a daily basis. The assimilation technique has been applied in an off-line mode since 17 October. Results based on bulk statistical verification of surface meteorology over the entire Southeastern US show that assimilating the GOES-derived land surface tendencies and solar radiation results in a significant reduction of the shelter air temperature and RH bias on a daily basis. In fact, the assimilation technique has produced improved temperature and RH forecasts for 97% of the 100 simulations performed to date. Work is currently underway to determine the sensitivity of the assimilation procedure to the availability of satellite data, length of assimilation period, model initialization, and synoptic-scale meteorological conditions. In addition, results from a detailed energy budget analysis using the Early Eta, our operational MM5, and the assimilation runs will help us to better understand the satellite assimilation the land-surface energy budge. Research during the spring-summer of 1999 will focus on the impact of the assimilation technique during the warm season where it is hypothesized that it can have a positive impact on QPF during conditions of weak synoptic-scale forcing.

Lapenta, William M.↗
DOE OSTI2017

Movement of the Melt Metal Layer under Conditions Typical of Transient Events in ITER

During the operation of ITER, protective coatings of the divertor and the first wall will be exposed to significant plasma heat loads which may cause a huge erosion. One of the major failure mechanisms of metallic armor is diminution of their thickness due to the melt layer displacement. New experimental data are required in order to develop and validate physical models of the melt layer movement. The paper presents the experiments where metal targets were irradiated by a plasma stream at the quasi-stationary high-current plasma accelerator QSPA-T. The obtained data allow one to determine the velocity and acceleration of the melt layer at various distances from the plasma stream axis. The force causing the radial movement of the melt layer is shown to create an acceleration whose order of magnitude is 1000g. The pressure gradient is not responsible for creating this large acceleration. To investigate the melt layer movement under a known force, the experiment with a rotating target was carried out. The influence of centrifugal and Coriolis forces led to appearance of curved elongated waves on the surface. The surface profile changed: there is no hill in the central part of the erosion crater in contrast to the stationary target. The experimental data clarify the trends in the melt motion that are required for development of theoretical models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

The Role of Deep Convection and Large-scale Circulation in Driving Model Spread in Low Cloud Feedback and Equilibrium Climate Sensitivity

This project aims to advance the understanding of the processes that drive the large uncertainties in climate change projections, use observations to constrain model physics and reduce the inter-model spread in equilibrium climate sensitivity (ECS). There are three major goals: 1) Characterize the representation of the physical pathways that link deep convection, large-scale circulation and low cloud feedback in CMIP6 model simulations and determine the relative contribution of each pathway to the CMIP6 model spread in low cloud feedback and ECS; 2) Use process-oriented diagnostics and multiple observations to evaluate CMIP6 model performance in capturing the observed cloud-circulation relation and deep convection characteristics including convective transition statistics and the bulk properties of mesoscale convective systems (MCSs). Error decomposition in CMIP6 models will be performed. 3) Conduct E3SM short-range hindcasts following the DOE Cloud-Associated Parameterizations Testbed (CAPT) protocol to pinpoint specific model parameters/processes that are crucial to the representation of deep convection, circulation, clouds and the pathways that connect them. We will modify convective parameters in E3SM and analyze the perturbed physics experiments (PPEs) to isolate model parameters that are critical to the uncertainty of ECS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evaluating the WFIP2 updates to the HRRR model using scanning Doppler lidar measurements in the complex terrain of the Columbia River Basin

The wind-energy (WE) industry relies on numerical weather prediction (NWP) forecast models as foundational or base models for many purposes, including wind-resource assessment and wind-power forecasting. During the Second Wind Forecast Improvement Project (WFIP2) in the Columbia River Basin of Oregon and Washington, a significant effort was made to improve NWP forecasts through focused model development, to include experimental refinements to the High Resolution Rapid Refresh (HRRR) model physics and horizontal grid spacing. In this study, the performance of an experimental version of HRRR that includes these refinements is tested against a control version, which corresponds to that of the operational HRRR run by National Oceanic and Atmospheric Administration/National Centers for Environmental Protection at the outset of WFIP2. Furthermore, the effects of horizontal grid resolution were also tested by comparing wind forecasts from the HRRR (with 3-km grid spacing) with those from a finer-resolution HRRR nest with 750-m grid spacing. Model forecasts are validated against accurate wind-profile measurements by three scanning, pulsed Doppler lidars at sites separated by a total distance of 71 km. Model skill and improvements in model skill, attributable to physics refinements and improved horizontal grid resolution, varied by season, by site, and during periods of atmospheric phenomena relevant to WE. In general, model errors were the largest below 150 m above ground level (AGL). Experimental HRRR refinements tended to reduce the mean absolute error (MAE) and other error metrics for many conditions, but degradation in skill (increased MAE) was noted below 150 m AGL at the two lowest-elevation sites at night. Finer resolution was found to produce the most significant reductions in the error metrics.

17 WIND ENERGY↗
NASA NTRS1994

A numerical analysis of shipboard and coastal zone color scanner time series of new production within Gulf Stream cyclonic eddies in the South Atlantic Bight

Eddy-induced upwelling occurs along the western edge of the Gulf Stream between Cape Canaveral, Florida, and Cape Hatteras, North Carolina, in the South Atlantic Bight (SAB). Coastal zone color scanner images of 1-km resolution spanning the period April 13-21, 1979, were processed to examine these eddy features in relation to concurrent shipboard and current/temperature measurements at moored arrays. A quasi-one-dimensional (z), time dependent biological model, using only nitrate as a nutrient source, has been combined with a three-dimensional physical model in an attempt to replicate the observed phytoplankton field at the northward edge of an eddy. The model is applicable only to the SAB south of the Charleston Bump, at approximately 31.5 deg N, since no feature analogous to the bump exists in the model bathymetry. The modeled chlorophyll, nitrate, and primary production fields of the euphotic zone are very similar to those obtained from the satellite and shipboard data at the leading edges of the observed eddies south of the Charleston Bump. The horizontal and vertical simulated fluxes of nitrate and chlorophyll show that only approximately 10% of the upwelled nitrate is utilized by the phytoplankton of the modeled grid box on the northern edge of the cyclone, while approximately 75% is lost horizontally, with the remainder still in the euphotic zone after the 10-day period of the model. Loss of chlorophyll due to sinking is very small in this strong upwelling region of the cyclone. The model is relatively insensitive to variations in the sinking parameterization and the external nitrate and chlorophyll fields but is very sensitive to a reduction of the maximum potential growth rate to half that measured. Given the success of this model in simulating the new production of the selcted upwelling region, other upwelling regions for which measurements or successful models of physical and biological quantities and rates exist could be modeled similarly.

Pribble, J. Raymond↗
DOE OSTI2017

Dimensionality reducibility for multi-physics reduced order modeling

Applications of reduced order modeling (ROM) to support analysis of complex reactor behavior using high fidelity simulations have developed rapidly in recent years. Reduction implies any computational approach aiming to reduce the cost of the simulation, especially for situations involving repeated executions such as probabilistic risk assessment and uncertainty quantification applications. This article presents a novel non-intrusive methodology to render reduction for multi-physics models by taking advantage of the combined reduction introduced by each sub-physics in the simulation. Next, a surrogate model is constructed in terms of the reduced dimensions. A key component of the proposed methodology is to upper-bound the errors resulting from the reduction to ensure its reliability for subsequent engineering applications. To implement and demonstrate the proposed ROM algorithm, the INL’s MAMMOTH environment is employed to analyze the level of reduction in the coupled radiation-thermal transport modeling of a 2D quarter fuel pin in a light water reactor spectrum. MAMMOTH couples the neutronics model of Rattlesnake module and the fuel performance model of BISON module. Here, the results show that the reduction obtained with coupled physics is more significant than that with individual sub-physics models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1992

Modeling and simulation of mobile satellite propagation

Mobile satellite systems are subject to severe fading due to blockage of the line-of-sight (LOS) path by roadside vegetation. A thorough understanding of the fading effects is necessary for the design of a reliable land mobile satellite system (LMSS). Analytical and empirical models are presented for predicting fade statistics for vegetative shadowing of mobile satellite terminals. A software simulator for generating simulated fade data is also presented. A physical model relating physical path parameters to propagation model parameters is presented, and results using the model are shown.

Barts, R. M.↗
NASA NTRSDate not supplied

Enabling in-time Prognostics with Surrogate Modeling through Physics-enhanced Dynamic Mode Decomposition Method

Computational models provide essential quantitative tools for assessing and predicting the health and performance of physical systems. However, high-fidelity models are rarely used in real-time operations or large optimization loops, due to their time-intensive nature. A common approach to improving computational efficiency of prognosis is to employ surrogate models. Such models can significantly decrease computation time for some accuracy loss. In this context, use of Dynamic Mode Decomposition (DMD) is proposed to generate surrogate models for lithium-ion (Li-ion) battery discharge. DMD has been suggested and used successfully in the area of fluid dynamics for over a decade, but it has not been applied to the PHM domain, where far-ahead prediction of nonlinear behavior is crucial to propagate faults or predict Remaining Useful Life (RUL). For Li-ion battery health management, the standard application of DMD using only the observable quantities of interest was unable to capture the nonlinear discharge of batteries exhibited in lab testing. The Koopman theory, however, provides a mechanism to tradeoff low dimensional nonlinear models with high-dimensional linear ones in a DMD framework, by augmenting nonlinear state variables into the system representation. In this way, DMD allows for configurable simulation accuracy dependent on the dimensionality of the Koopman operator. For battery health management, we augmented the observable variables with the hidden states of a higher-fidelity physics model to build the DMD surrogate. In comparison to a high-fidelity model, the surrogate improved computational efficiency with only a minimal loss of accuracy, and enabled long-term prognostics horizons. A generalized method for this was implemented in the prog models python package.

prognostics and health management↗
NASA NTRSDate not supplied

Hybrid Approaches to Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Systems Health Management↗
DOE OSTI2022

Initial development of a generic fluoride salt-cooled reactor model

Fluoride high-temperature reactors (FHRs) are high-temperature, low-pressure reactor concepts that use tri-structural isotropic (TRISO) fuel and molten fluoride salt coolant. These reactors have the potential to provide both electrical power and high-temperature process heat. We used generic FHR parameters for a pebble-bed FHR to develop an initial model with fresh fuel for a generic FHR (gFHR) in MELCOR and SCALE (NEWT and KENO). In this paper, we present the development of our gFHR models, which will serve as the baseline for a sensitivity and uncertainty analysis to quantify the range of possible source terms for FHRs in severe accidents. We present MELCOR results for fuel and coolant temperatures through the core, a nodalization study for the steady-state thermal hydraulic model, and development of reactor physics models in SCALE. As this work progresses, these models will be used to calculate source terms for a loss-of-forced-flow accident and to conduct a sensitivity study on this accident to establish a range of possible source terms. SCALE will provide reactor physics parameters like isotopic inventory, decay heat generation, and temperature coefficients of reactivity. Using the uncertainty quantification tools within SCALE, we will generate distributions for those parameters and will use the uncertainty quantification code RAVEN or DAKOTA to sample those distributions in MELCOR to quantify the impact of reactor physics and thermal hydraulic uncertainties on FHR source terms. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

Studies of rare B hadron decays to leptons at hadron colliders

Rare B hadron decays provide an excellent test bench for the Standard Model and can probe new physics models. We review the experimental progress of the searches for rare leptonic B decays ($b\rightarrow \ell^+ \ell^-$ and $b\rightarrow s \ell^+ \ell^-$) at LHC and Tevatron experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Comparison of kinetic and extended magnetohydrodynamics computational models for the linear ion temperature gradient instability in slab geometry

We perform linear stability studies of the ion temperature gradient (ITG) instability in unsheared slab geometry using kinetic and extended magnetohydrodynamics (MHD) models, in the regime k{sub ∥}/k{sub ⊥}≪1. The ITG is a parallel (to B) sound wave that may be destabilized by finite ion Larmor radius (FLR) effects in the presence of a gradient in the equilibrium ion temperature. The ITG is stable in both ideal and resistive MHD; for a given temperature scale length L{sub Ti0}, instability requires that either k{sub ⊥}ρ{sub i} or ρ{sub i}/L{sub Ti0} be sufficiently large. Kinetic models capture FLR effects to all orders in either parameter. In the extended MHD model, these effects are captured only to lowest order by means of the Braginskii ion gyro-viscous stress tensor and the ion diamagnetic heat flux. We present the linear electrostatic dispersion relations for the ITG for both kinetic Vlasov and extended MHD (two-fluid) models in the local approximation. In the low frequency fluid regime, these reduce to the same cubic equation for the complex eigenvalue ω=ω{sub r}+iγ. An explicit solution is derived for the growth rate and real frequency in this regime. These are found to depend on a single non-dimensional parameter. We also compute the eigenvalues and the eigenfunctions with the extended MHD code NIMROD, and a hybrid kinetic δf code that assumes six-dimensional Vlasov ions and isothermal fluid electrons, as functions of k{sub ⊥}ρ{sub i} and ρ{sub i}/L{sub Ti0} using a spatially dependent equilibrium. These solutions are compared with each other, and with the predictions of the local kinetic and fluid dispersion relations. Kinetic and fluid calculations agree well at and near the marginal stability point, but diverge as k{sub ⊥}ρ{sub i} or ρ{sub i}/L{sub Ti0} increases. There is good qualitative agreement between the models for the shape of the unstable global eigenfunction for L{sub Ti0}/ρ{sub i}=30 and 20. The results quantify how far fluid calculations can be extended accurately into the kinetic regime. We conclude that for the linear ITG problem in slab geometry with unsheared magnetic field when k{sub ∥}/k{sub ⊥}≪1, the extended MHD model may be a reliable physical model for this problem when ρ{sub i}/L{sub Ti0}<10{sup −2} and k{sub ⊥}ρ{sub i}<0.2.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Prospecting for new physics in the Higgs and flavor sectors

We explore two directions in beyond the standard model physics: dark matter model building and probing new sources of CP violation. In dark matter model building, we consider two scenarios where the stability of dark matter derives from the flavor symmetries of the standard model. The first model contains a flavor singlet dark matter candidate whose couplings to the visible sector are proportional to the flavor breaking parameters. This leads to a metastable dark matter with TeV scale mediators. In the second model, we consider a fully gauged SU(3) 3 flavor model with a flavor triplet dark matter. Consequently, the dark matter multiplet is charged while the standard model fields are neutral under a remnant Z 3 which ensures dark matter stability. We show that a Dirac fermion dark matter with radiative splitting in the multiplet must have a mass in the range [0:5; 5] TeV in order to satisfy all experimental constraints. We then turn our attention to Higgs portal dark matter and investigate the possibility of obtaining bounds on the up, down, and strange quark Yukawa couplings. If Higgs portal dark matter is discovered, we find that direct detection rates are insensitive to vanishing light quark Yukawa couplings. We then review flavor models and give the expected enhancement or suppression of the Yukawa couplings in those models. Finally, in the last two chapters, we develop techniques for probing CP violation in the Higgs coupling to photons and in rare radiative decays of B mesons. While theoretically clean, we find that these methods are not practical with current and planned detectors. However, these techniques can be useful with a dedicated detector (e.g., a gaseous TPC). In the case of radiative B meson decay B 0 → (K* → Kππ) γ, the techniques we develop also allow the extraction of the photon polarization fraction which is sensitive to new physics contributions since, in the standard model, the right(left) handed polarization fraction is of O( Λ QCD =m b ) for $\bar{B}^{0}$(B 0 ) meson decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Reverberation mapping of the broad line region: application to a hydrodynamical line-driven disk wind solution

The latest analysis efforts in reverberation mapping are beginning to allow reconstruction of echo images (or velocity-delay maps) that encode information about the structure and kinematics of the broad line region (BLR) in active galactic nuclei (AGNs). Such maps can constrain sophisticated physical models for the BLR. The physical picture of the BLR is often theorized to be a photoionized wind launched from the AGN accretion disk. Previously we showed that the line-driven disk wind solution found in an earlier simulation by Proga and Kallman is virialized over a large distance from the disk. This finding implies that, according to this model, black hole masses can be reliably estimated through reverberation mapping techniques. However, predictions of echo images expected from line-driven disk winds are not available. Here, after presenting the necessary radiative transfer methodology, we carry out the first calculations of such predictions. We find that the echo images are quite similar to other virialized BLR models such as randomly orbiting clouds and thin Keplerian disks. We conduct a parameter survey exploring how echo images, line profiles, and transfer functions depend on both the inclination angle and the line opacity. We find that the line profiles are almost always single peaked, while transfer functions tend to have tails extending to large time delays. The outflow, despite being primarily equatorially directed, causes an appreciable blueshifted excess on both the echo image and line profile when seen from lower inclinations (i≲45{sup ∘}). This effect may be observable in low ionization lines such as Hβ.

79 ASTRONOMY AND ASTROPHYSICS↗