Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “forward modeling”

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.

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

At least 613 records · Page 34

Feed-Forward Compensation for Model Predictive Control in Tri-port Current-Source Medium-Voltage String Inverters for PV-Plus-Storage Farms

The novel tri-port current-source medium-voltage string inverter (TCS-MVSI) is a promising candidate for large-scale PV-plus-storage (PVS) farms owing to its galvanic isolation, easy storage integration, soft-switching capability across entire load range, controlled low dv/dt and EMI, benign fault tolerance, etc. Due to its low inertia feature, traditional PI-based control cannot manage large transients effectively. Instead, a model-based predictive control (MPC) is proposed to achieve robust and stable operation. As is well known, the control performance of MPC is compromised by the sampling and computational delay during implementation significantly, if not well addressed. This paper analyzed and quantified these delays and then proposes feed-forward compensation (FFC) for the MPC method to compensate the delays and the large parameter variations due to the low-inertia nature. In addition, this method also compensates for the high dc-link ripple within each switching cycle, a unique issue for low-inertia converters. Here, the proposed method requires low computational effort, allowing it to be extended for multiple ports. The effectiveness of the proposed method has been validated in experiments. In 10 kW test, the proposed method decreases the average dc-link current by 17%, leading to ~20% conduction losses and ~0.5% increase in converter efficiency. In addition, the peak dc-link current also decreases by 15%, resulting in reduced transformer size. As a result, an increased power density can be achieved with the proposed method. Similar improvements have been observed across the power range from 2 kW to 10 kW.

30 DIRECT ENERGY CONVERSION↗

A survey of particle measurements in the Arctic from the Forward Scattering Spectrometer Probe model 300

A new instrument, the Forward Scattering Spectrometer Probe (FSSP) 300, was used on the NASA ER-2 during the Airborne Arctic Stratospheric Expedition (AASE) to count and size particles in the size range 0.4-24 microns in diameter. A brief description of the instrument is presented, and observations for each ER-2 flight are summarized. Measurements were made in both type I and type II polar stratospheric clouds as well as in the background sulfuric-acid particles. Total particle concentrations up to 16/cu cm with total particle volumes up to 10 cubic micron/cu cm were observed in some of the polar-stratospheric-cloud events.

Dye, J. E.↗

Modeling the Path Forward for Marine Energy

Today's marine energy industry is at an exciting turning point. Companies are testing out their early-stage prototypes - designed to harness the clean energy in ocean and river waves, currents, and tides - in their first open-water trials. But while such trials are a necessary step toward commercialization, they can come with high costs and risk if the deployments do not go as planned.

data modeling↗

Linearization of manipulator dynamics using spatial operators

Linearized dynamics models for manipulators are useful in robot analysis, motion planning, and control applications. Techniques from the spatial operator algebra are used to obtain closed form operator expressions for two types of linearized dynamics models, the linearized inverse and forward dynamics models. Spatially recursive algorithms of O(n) and O(n-squared) complexity for the computation of the perturbation vector and coefficient matrices for the linearized inverse dynamics model are developed first. Subsequently, operator factorization and inversion identities are used to develop corresponding closed-form expressions for the linearized forward dynamics model (LFDM). Once again, these are used to develop algorithms of O(n) and O(n-squared) complexity for the computation of the perturbation vector and the coefficient matrices. The algorithms for the LFDM do not require the explicit computation of the mass matrix nor its numerical inversion and are also of lower complexity than the conventional O(n-cubed) algorithms.

Jain, A.↗

Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction

4D time-space reconstruction of dynamic events or deforming objects using X-ray computed tomography (CT) is an important inverse problem in non-destructive evaluation. Conventional back-projection based reconstruction methods assume that the object remains static for the duration of several tens or hundreds of X-ray projection measurement images (reconstruction of consecutive limited-angle CT scans). However, this is an unrealistic assumption for many in-situ experiments that causes spurious artifacts and inaccurate morphological reconstructions of the object. To solve this problem, we propose to perform a 4D time-space reconstruction using a distributed implicit neural representation (DINR) network that is trained using a novel distributed stochastic training algorithm. Our DINR network learns to reconstruct the object at its output by iterative optimization of its network parameters such that the measured projection images best match the output of the CT forward measurement model. Here, we use a forward measurement model that is a function of the DINR outputs at a sparsely sampled set of continuous valued 4D object coordinates. Unlike previous neural representation architectures that forward and back propagate through dense voxel grids that sample the object's entire time-space coordinates, we only propagate through the DINR at a small subset of object coordinates in each iteration resulting in an order-of-magnitude reduction in memory and compute for training. DINR leverages distributed computation across several compute nodes and GPUs to produce high-fidelity 4D time-space reconstructions. We use both simulated parallel-beam and experimental cone-beam X-ray CT datasets to demonstrate the superior performance of our approach.

36 MATERIALS SCIENCE↗

Helicopter local blade circulation calculations for a model rotor in forward flight using laser velocimeter measurements

A program is described whose purpose was to develop the measurement and data processing techniques necessary to accurately compute the local rotor blade circulation at any azimuth and radius in a wind tunnel environment at representative forward speeds. With these techniques, further tests using a complex rotor system with local surface pressure measurements should help to determine the accuracy of the technique for general applications to rotor blade span-load measurement programs in wind tunnel forward flight conditions. Preliminary calculations are reported.

Hoad, Danny R.↗

A Bayesian approach to microwave precipitation profile retrieval

A multichannel passive microwave precipitation retrieval algorithm is developed. Bayes theorem is used to combine statistical information from numerical cloud models with forward radiative transfer modeling. A multivariate lognormal prior probability distribution contains the covariance information about hydrometeor distribution that resolves the nonuniqueness inherent in the inversion process. Hydrometeor profiles are retrieved by maximizing the posterior probability density for each vector of observations. The hydrometeor profile retrieval method is tested with data from the Advanced Microwave Precipitation Radiometer (10, 19, 37, and 85 GHz) of convection over ocean and land in Florida. The CP-2 multiparameter radar data are used to verify the retrieved profiles. The results show that the method can retrieve approximate hydrometeor profiles, with larger errors over land than water. There is considerably greater accuracy in the retrieval of integrated hydrometeor contents than of profiles. Many of the retrieval errors are traced to problems with the cloud model microphysical information, and future improvements to the algorithm are suggested.

Evans, K. Franklin↗

Expected Performance of Ozone Climate Data Records from Ozone Mapping and Profiler Suite Limb Profiler

The Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP) was launched on board of the Soumi NPP space platform in late October 2011. It provides ozone-profiling capability with high-vertical resolution from 60 Ian to cloud top. In this study, an end-to-end Observing System Simulation Experiment (OSSE) of OMPS/LP ozone is discussed. The OSSE was developed at NASA's Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System (GEOS-5) data assimilation system. The "truth" for this OSSE is built by assimilating MLS profiles and OMI ozone columns, which is known to produce realistic three-dimensional ozone fields in the stratosphere and upper troposphere. OMPS/LP radiances were computed at tangent points computed by an appropriate orbital model. The OMPS/LP forward RT model, Instrument Models (IMs) and EDR retrieval model were introduced and pseudo-observations derived. The resultant synthetic OMPS/LP observations were evaluated against the "truth" and subsequently these observations were assimilated into GEOS-5. Comparison of this assimilated dataset with the "truth" enables comparisons of the likely uncertainties in 3-D analyses of OMPS/LP data. This study demonstrated the assimilation capabilities of OMPS/LP ozone in GEOS-5, with the monthly, zonal mean (O-A) smaller than 0.02ppmv at all levels, the nns(O-A) close to O.lppmv from 100hPa to 0.2hPa; and the mean(O-B) around the 0.02ppmv for all levels. The monthly zonal mean analysis generally agrees to within 2% of the truth, with larger differences of 2-4% (0.1-0.2ppmv) around 10hPa close to North Pole and in the tropical tropopause region, where the difference is above 20% due to the very low ozone concentrations. These OSSEs demonstrated that, within a single data assimilation system and the assumption that assimilated MLS observations provide a true rendition of the stratosphere, the OMPS/LP ozone data are likely to produce accurate analyses through much of the stratosphere. Additional studies are needed to evaluate the importance of the extremely high vertical resolution of the OMPS/LP ozone data

Xu, P. Q.↗

NASA's Global Precipitation Mission Ground Validation Segment

NASA is designing a Ground Validation Segment (GVS) as one of its contributions to the Global Precipitation Measurement (GPM) mission. The GPM GVS provides an independent means for evaluation, diagnosis, and ultimately improvement of the GPM spaceborne measurements and precipitation products. NASA's GPM GVS concept calls for a combination of direct observations executed within a Multidimensional Observing Volume (MOV) and model-based analyses executed by a Satellite Simulator Model (SSM). The MOV consists of ground-based instruments that measure local surface and atmospheric properties required for GPM validation. The SSM utilizes MOV measurements in a forward numerical model. The goal of the SSM forward modeling is calculation of the following properties: top-of-atmosphere microwave radiative quantities to within sensor noise of those measured by the GPM Core Satellite, precipitation quantities identical to those generated by the standard GPM precipitation retrieval algorithms, and quantitative/objective error estimates of both sets of quantities. At present, the GVS is in the early design stage and various scenarios have been generated to assess how it will be used in the GPM era. The GPM GVS will be operational in the year prior to the launch of the GPM core satellite, which has a launch date scheduled for December 2010.

GVS (GROUND VALIDATION SEGMENT)↗

Unifying radiative transfer models in computer graphics and remote sensing, Part I: A Survey

The constellation of Earth-observing satellites continuously collects measurements of scattered radiance, which must be transformed into geophysical parameters in order to answer fundamental scientific questions about the Earth. Retrieval of these parameters requires highly flexible, accurate, and fast forward and inverse radiative transfer models. Existing forward models used by the remote sensing community are typically accurate and fast, but sacrifice flexibility by assuming the atmosphere or ocean is composed of plane-parallel layers. Monte Carlo forward models can handle more complex scenarios such as 3D spatial heterogeneity, but are relatively slower. We propose looking to the computer graphics community for inspiration to improve the statistical efficiency of Monte Carlo forward models and explore new approaches to inverse models for remote sensing. In Part 1 of this work, we examine the evolution of radiative transfer models in computer graphics and highlight recent advancements that have the potential to push forward models in remote sensing beyond their current periphery of realism.

Radiative transfer↗

Fitting a Two-Component Scattering Model to Polarimetric SAR Data from Forests

Two simple scattering mechanisms are fitted to polarimetric synthetic aperture radar (SAR) observations of forests. The mechanisms are canopy scatter from a reciprocal medium with azimuthal symmetry and a ground scatter term that can represent double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants or Bragg scatter from a moderately rough surface, which is seen through a layer of vertically oriented scatterers. The model is shown to represent the behavior of polarimetric backscatter from a tropical forest and two temperate forest sites by applying it to data from the National Aeronautic and Space Agency/Jet Propulsion Laboratory's Airborne SAR (AIRSAR) system. Scattering contributions from the two basic scattering mechanisms are estimated for clusters of pixels in polarimetric SAR images. The solution involves the estimation of four parameters from four separate equations. This model fit approach is justified as a simplification of more complicated scattering models, which require many inputs to solve the forward scattering problem. The model is used to develop an understanding of the ground-trunk double-bounce scattering that is present in the data, which is seen to vary considerably as a function of incidence angle. Two parameters in the model fit appear to exhibit sensitivity to vegetation canopy structure, which is worth further exploration. Results from the model fit for the ground scattering term are compared with estimates from a forward model and shown to be in good agreement. The behavior of the scattering from the ground-trunk interaction is consistent with the presence of a pseudo-Brewster angle effect for the air-trunk scattering interface. If the Brewster angle is known, it is possible to directly estimate the real part of the dielectric constant of the trunks, a key variable in forward modeling of backscatter from forests. It is also shown how, with a priori knowledge of the forest height, an estimate for the attenuation coefficient of the canopy can be obtained directly from the multi-incidence-angle polarimetric observations. This attenuation coefficient is another key variable in forward models and is generally related to the canopy density.

temperate forests↗

An Integrated Snow Radiance and Snow Physics Modeling Framework for Cold Land Surface Modeling

Recent developments in forward radiative transfer modeling and physical land surface modeling are converging to allow the assembly of an integrated snow/cold lands modeling framework for land surface modeling and data assimilation applications. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. Together these form a flexible framework for self-consistent remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. Each element of this framework is modular so the choice of element can be tailored to match the emphasis of a particular study. For example, within our framework, four choices of a FRTM are available to simulate the brightness temperature of snow: Two models are available to model the physical evolution of the snowpack and underlying soil, and two models are available to handle the water/energy balance at the land surface. Since the framework is modular, other models-physical or statistical--can be accommodated, too. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster at the NASA Goddard Space Flight Center. The advantages of such an integrated modular framework built on the LIS will be described through examples-e.g., studies to analyze snow field experiment observations, and simulations of future satellite missions for snow and cold land processes.

Kim, Edward J.↗

A remanent and induced magnetization model of Magsat vector anomalies over the west African craton

Scalar and vector Magsat anomalies over the west African craton are analyzed by forward and inverse models. A forward model of the Man shield is based on Liberia. Induced magnetization contrasts due to sporadic iron-formations and to regional metamorphic rocks, and a contrast in remanent magnetization within the lower crust are included. This combination reproduces the location, magnitude and adopted local zero level of anomalies in the initial Magsat maps. An inverse model of the Reguibat shield estimates the magnetization contrast of its lithosphere, and when magnetism is restricted to shallower than 75 km both shields can be represented by a susceptibility contrast of +0.02. A residual anomaly between the shields involves a relative deficiency of induced magnetization along with other causes.

Toft, P. B.↗

Aerodynamic characteristics of a large scale lift fan transport model with podded fans forward and lift cruise fans mounted above the wing

The aerodynamic characteristics of a large scale V/STOL transport model powered by tip-turbine driven lift fans were investigated. The model had four fans; the forward fans were mounted in pods forward of the wing at midsemispan. The aft fans were placed in cruise nacelles behind and above the wing. A cascade of variable camber exit louvers was placed behind each of the lift-cruise fans to turn the fan flow in the lift direction for hover and transition to wing supported flight. The wing of the model was mounted above the fuselage, had an aspect ratio of 5.8, sweepback of 35 deg at the quarter chord line and a taper ratio of 0.3. Various configurations of the model were tested to explore the transition speed range. Fan performance, turning effectiveness of the variable camber exit louvers, longitudinal and lateral-directional characteristics with fan operation in crossflow are presented.

Kirk, J. V.↗

The Impacts of Fossil Fuel Emission Uncertainties and Accounting for 3-D Chemical CO2 Production on Inverse Natural Carbon Flux Estimates from Satellite and In Situ Data

Atmospheric carbon dioxide (CO2) inversions for estimating natural carbon fluxes typically do not allow for adjustment of fossil fuel CO2 emissions, despite significant uncertainties in emission inventories and inadequacies in the specification of international bunker emissions in inversions. Also, most inversions place CO2 release from fossil fuel combustion and biospheric sources entirely at the surface. However, a non-negligible portion of the emissions actually occurs in the form of reduced carbon species, which are eventually oxidized to CO2 downwind. Omission of this ‘chemical pump’ can result in a significant redistribution of the inferred total carbon fluxes among regions. We assess the impacts of different prescriptions of fossil fuel emissions and accounting for the chemical pump on flux estimation, with a novel aspect of conducting both satellite CO2 observation-based and surface in situ-based inversions. We apply 3-D carbon monoxide (CO) loss rates archived from a state-of-the-art GEOS chemistry and climate model simulation in a forward transport model run to simulate the distribution of CO2 originating from oxidation of carbon species. We also subtract amounts from the prior surface CO2 fluxes that are actually emitted in the form of fossil and biospheric CO, methane, and nonmethane volatile organic compounds (VOCs). We find that the posterior large-scale fluxes are generally insensitive to the finer-scale spatial differences between the ODIAC and CDIAC fossil fuel CO2 gridded datasets and assumptions about international bunker emissions. However, accounting for 3-D chemical CO2 production and the surface correction shifts the global carbon sink, e.g., from land to ocean and from the tropics to the north, with a magnitude and even direction that depend on assumptions about the surface correction. A GOSAT satellite-based inversion is more sensitive to the chemical pump than one using in situ observations, exhibiting substantial flux impacts of 0.28, 0.53, and -0.47 Pg C yr(exp -1) over tropical land, global land, and oceans, due to differences in the horizontal and vertical sampling of the wo observation types. Overall, the biases from neglecting the chemical pump appear to be minor relative to the flux estimate uncertainties and the differences between the in situ and GOSAT inversions, but their relative importance will grow in the future as observational coverage further increases and satellite retrieval biases decrease.

James S Wang↗