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At least 739 records · Page 41

River and lake ice conditions as determined from AIRSAR imagery

Synthetic aperture radar (SAR) imagery data can provide information on types and distribution of river and lake ice needed for studying river ice processes and dynamics, monitoring ice during winter navigation, and formulating ice control strategies. Visible and IR remote sensing systems cannot provide such data and present field methods are inadequate for characterizing ice conditions over long river reaches. Our ongoing analysis of JPL's AIRSAR imagery data and concurrent ground truth of ice conditions on the Tanana River and surrounding lakes near Fairbanks, Alaska, in March 1988, has resulted in several findings: hummocked ice covers and zones of variable ice surface roughness within them can be differentiated; C- and L-band data are more sensitive than P-band to the range of surface roughnesses encountered; smooth, level ice that is clear or contains small bubbles produces little backscatter; snow-covered river ice, whether rough or smooth, is distinguishable from snow-covered river sediments on exposed river beds and unvegetated bars; and open water leads are readily distinguished.

Melloh, Rae A.↗

Tests of two convection theories for red giant and red supergiant envelopes

Two theories of stellar envelope convection are considered here in the context of red giants and red supergiants of intermediate to high mass: Boehm-Vitense's standard mixing-length theory (MLT) and Canuto & Mazzitelli's new theory incorporating the full spectrum of turbulence (FST). Both theories assume incompressible convection. Two formulations of the convective mixing length are also evaluated: l proportional to the local pressure scale height (H(sub P)) and l proportional to the distance from the upper boundary of the convection zone (z). Applications to test both theories are made by calculating stellar evolutionary sequences into the red zone (z). Applications to test both theories are made by calculating stellar evolutionary sequences into the red phase of core helium burning. Since the theoretically predicted effective temperatures for cool stars are known to be sensitive to the assigned value of the mixing length, this quantity has been individually calibrated for each evolutionary sequence. The calibration is done in a composite Hertzsprung-Russell diagram for the red giant and red supergiant members of well-observed Galactic open clusters. The MLT model requires the constant of proportionality for the convective mixing length to vary by a small but statistically significant amount with stellar mass, whereas the FST model succeeds in all cases with the mixing lenghth simply set equal to z. The structure of the deep stellar interior, however, remains very nearly unaffected by the choices of convection theory and mixing lenghth. Inside the convective envelope itself, a density inversion always occurs, but is somewhat smaller for the convectively more efficient MLT model. On physical grounds the FST model is preferable, and seems to alleviate the problem of finding the proper mixing length.

Stothers, Richard B.↗

The Nasa Multiscale Analysis Tool: an Enabling Platform for Achieving Vision 2040

Vision 2040 is a community-driven consensus document, written in 2018, aimed at defining the potential 25-year future state required for performing integrated multiscale modeling of materials and systems for future aerospace and aeronautical applications. Nine Vision Key Elements (KEs) were defined along with associated technical gaps. This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT). This paper will specifically focus on NASMAT’s ability to address gaps in three of the nine Vision 2040 KEs: 1) Models and Methods, 2) Multiscale Measurements and Characterization Tools and Methods, and 6) Data, Informatics, and Visualization. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials. NASMAT offers the user flexibility to define an arbitrary number of length scales (levels) where a variety of micromechanics theories can be implemented at each level. Micromechanics theories can be selected to balance accuracy and computational efficiency and range from analytical (Mori-Tanaka) to several semi-analytical (method of cells) formulations. NASMAT can also be coupled with external software and used to perform multiscale analyses of more complex structures. The paper will include a recent application of NASMAT to model a complex, three-dimensional woven composite, with a particular emphasis placed on multiscale measurements utilized to enhance the quality of the multiscale analysis. Since typical NASMAT analyses can be completed in on the order of seconds to minutes, a second example will demonstrate NASMAT’s ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on developing multiscale data visualization tools will also be addressed along with the challenges associated with and proposed solutions for sifting through large amounts of data. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.

Vision 2040↗

Extended Lagrangian Born–Oppenheimer molecular dynamics using a Krylov subspace approximation

It is shown how the electronic equations of motion in extended Lagrangian Born–Oppenheimer molecular dynamics simulations can be integrated using low-rank approximations of the inverse Jacobian kernel. This kernel determines the metric tensor in the harmonic oscillator extension of the Lagrangian that drives the evolution of the electronic degrees of freedom. The proposed kernel approximation is derived from a pseudoinverse of a low-rank estimate of the Jacobian, which is expressed in terms of a generalized set of directional derivatives with directions that are given from a Krylov subspace approximation. The approach allows a tunable and adaptive approximation that can take advantage of efficient preconditioning techniques. The proposed kernel approximation for the integration of the electronic equations of motion makes it possible to apply extended Lagrangian first-principles molecular dynamics simulations to a broader range of problems, including reactive chemical systems with numerically sensitive and unsteady charge solutions. This can be achieved without requiring exact full calculations of the inverse Jacobian kernel in each time step or relying on iterative non-linear self-consistent field optimization of the electronic ground state prior to the force evaluations as in regular direct Born–Oppenheimer molecular dynamics. We note the low-rank approximation of the Jacobian is directly related to Broyden’s class of quasi-Newton algorithms and Jacobian-free Newton–Krylov methods and provides a complementary formulation for the solution of nonlinear systems of equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Probabilistic Fracture Mechanics Analysis of the Orbiter's LH2 Feedline Flowliner

Work performed by Southwest Research Institute (SwRI) as part of an Independent Technical Assessment (ITA) for the NASA Engineering and Safety Center (NESC) is summarized. The ITA goal was to establish a flight rationale in light of a history of fatigue cracking due to flow induced vibrations in the feedline flowliners that supply liquid hydrogen to the space shuttle main engines. Prior deterministic analyses using worst-case assumptions predicted failure in a single flight. The current work formulated statistical models for dynamic loading and cryogenic fatigue crack growth properties, instead of using worst-case assumptions. Weight function solutions for bivariant stressing were developed to determine accurate crack "driving-forces". Monte Carlo simulations showed that low flowliner probabilities of failure (POF = 0.001 to 0.0001) are achievable, provided pre-flight inspections for cracks are performed with adequate probability of detection (POD)-specifically, 20/75 mils with 50%/99% POD. Measurements to confirm assumed POD curves are recommended. Since the computed POFs are very sensitive to the cyclic loads/stresses and the analysis of strain gage data revealed inconsistencies with the previous assumption of a single dominant vibrant mode, further work to reconcile this difference is recommended. It is possible that the unaccounted vibrational modes in the flight spectra could increase the computed POFs.

Bonacuse, Peter J.↗

Simulations of a Liquid Hydrogen Inducer at Low-Flow Off-Design Flow Conditions

The ability to accurately model details of inlet back flow for inducers operating a t low-flow, off-design conditions is evaluated. A sub-scale version of a three-bladed liquid hydrogen inducer tested in water with detailed velocity and pressure measurements is used as a numerical test bed. Under low-flow, off-design conditions the length of the separation zone as well as the swirl velocity magnitude was under predicted with a standard k-E model. When the turbulent viscosity coefficient was reduced good comparison was obtained a t all the flow conditions examined with both the magnitude and shape of the profile matching well with the experimental data taken half a diameter upstream of the leading edge. The velocity profiles and incidence angles a t the leading edge itself were less sensitive to the back flow length predictions indicating that single-phase performance predictions may be well predicted even if the details of flow separation modeled are incorrect. However, for cavitating flow situations the prediction of the correct swirl in the back flow and the pressure depression in the core becomes critical since it leads to vapor formation. The simulations have been performed using the CRUNCH CFD(Registered Trademark) code that has a generalized multi-element unstructured framework and a n advanced multi-phase formulation for cryogenic fluids. The framework has been validated rigorously for predictions of temperature and pressure depression in cryogenic fluid cavities and has also been shown to predict the cavitation breakdown point for inducers a t design conditions.

Hosangadi, A.↗

Efficient proactive vehicle relocation for on-demand mobility service with recurrent neural networks

One major challenge for on-demand mobility service (OMS) providers is to seamlessly match empty vehicles with trip requests so that the total vacant mileage is minimized. In this work, we develop an innovative data-driven approach for devising efficient vehicle relocation policy for OMS that (1) proactively relocates vehicles before the demand is observed and (2) reduces the inequality among drivers' income so that the proactive relocation policy is fair and is likely to be followed by drivers. Our approach represents the fusion of optimization and machine learning methods, which comprises three steps: First, we formulate the optimal proactive relocation as an optimal/stable matching problems and solve for global optimal solutions based on historical data. Second, the optimal solutions are then grouped and fed to train the deep learning models which consist of fully connected layers and long short-term memory networks. Low rank approximation is introduced to reduce the model complexity and improve the training performances. Finally, we use the trained model to predict the relocation policy which can be implemented in real time. We conduct comprehensive numerical experiments and sensitivity analyses to demonstrate the performances of the proposed method using New York City taxi data. Here, the results suggest that our method will reduce empty mileage per trip by 54-70% under optimal matching strategy, and a 25-32% reduction can also be achieved by following stable matching strategy. We also validate that the predicted relocation policies are robust in the presence of uncertain passenger demand level and passenger trip-requesting behavior.

33 ADVANCED PROPULSION SYSTEMS↗

The Fabrication of an Evanescent Field Sensor

We present current results concerning novel sensor-based applications for tilted angle fiber Bragg gratings summarized in a recently filed patent. In addition, concepts involving the coupling of light out of the core region of an optical fiber using ablated corrugations to induce interactions with the surrounding media will also be discussed. The interactions between the media and the coupled light formulate the sensing mechanism for both of these devices. The research illustrated here is an extension of previous work that investigated the affects of intense UV radiation fields on both SiO2 and Ge-doped SiO2-based structures (specifically optical fibers and preforms). Finally, these sensors were devised in order to satisfy an experimental task set forth by NASA Glenn involving the production of a prototype evanescent field sensor capable of real-time, dynamic index of refraction measurements as well as early (ultra-high sensitivity) detection of icing on airplane wings.

Lyons, Donald R.↗

An Enabling Platform for Achieving Multiscale Multiphysics Analysis of Multiphase Materials

This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT) which address technical gaps in three of the Vision 2040 key discipline areas. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials and is available free through the NASA software catalog. It offers the user flexibility to define an arbitrary number of length scales (levels) where a variety of micromechanics theories can be implemented at each level. Micromechanics theories can be selected to balance accuracy and computational efficiency and range from analytical (Mori-Tanaka) to several semi-analytical (method of cells) formulations. The resulting anisotropic, evolving nonlinear, thermomechanical constitutive model can also be coupled with external software and used to perform multiscale analyses of more complex structures. A recent application to model a complex, three-dimensional woven composite, with a particular emphasis placed on multiscale measurements utilized to enhance the quality of the multiscale analysis will be discussed. Since typical NASMAT analyses can be completed on the order of seconds to minutes, a second example will demonstrate the ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on implementing NASMAT within a multiscale digital thread/digital twin framework will also be addressed. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.

Multiscale↗

Calibration of elastoplastic constitutive model parameters from full-field data with automatic differentiation-based sensitivities

Here, we present a framework for calibration of parameters in elastoplastic constitutive models that is based on the use of automatic differentiation (AD). The model calibration problem is posed as a partial differential equation-constrained optimization problem where a finite element (FE) model of the coupled equilibrium equation and constitutive model evolution equations serves as the constraint. The objective function quantifies the mismatch between the displacement predicted by the FE model and full-field digital image correlation data, and the optimization problem is solved using gradient-based optimization algorithms. Forward and adjoint sensitivities are used to compute the gradient at considerably less cost than its calculation from finite difference approximations. Through the use of AD, we need only to write the constraints in terms of AD objects, where all of the derivatives required for the forward and inverse problems are obtained by appropriately seeding and evaluating these quantities. We present three numerical examples that verify the correctness of the gradient, demonstrate the AD approach's parallel computation capabilities via application to a large-scale FE model, and highlight the formulation's ease of extensibility to other classes of constitutive models.

42 ENGINEERING↗

The derivation of parent electron spectra from bremsstrahlung hard X-ray spectra

A numerical method is formulated to derive the spectrum of the parent electrons from the hard X-ray spectrum produced in optically thin bremsstrahlung. The method can utilize any form for the bremsstrahlung cross sections, and it provides accurate estimates of uncertainties in the derived electron spectrum based on uncertainties in the photon measurements. This method is applied to test photon spectra, as well as to hard X-ray spectra of the June 27, 1980 solar flare which was observed by high spectral resolution detectors. Future measurements with much more sensitive detectors will enable this method to be used to derive detailed, accurate flare electron spectra.

Johns, Christopher M.↗

Bayesian Adaptive Polynomial Chaos Expansions

Polynomial chaos expansions (PCEs) are widely used for uncertainty quantification (UQ) tasks, particularly in the applied mathematics community. However, PCE has received comparatively less attention in the statistics literature, and fully Bayesian formulations remain rare—especially with implementations in R. Motivated by the success of adaptive Bayesian machine learning models such as BART, BASS and BPPR, we develop a new fully Bayesian adaptive PCE method with an efficient and accessible R implementation: khaos. Our approach includes a novel proposal distribution that enables data-driven interaction selection and supports a modified g-prior tailored to PCE structure. Through simulation studies and real-world UQ applications, we demonstrate that the Bayesian adaptive PCE provides competitive performance for surrogate modeling, global sensitivity analysis and ordinal regression tasks.

97 MATHEMATICS AND COMPUTING↗

Determining the profitability of energy storage over its life cycle using levelized cost of storage

Levelized cost of storage (LCOS) can be a simple, intuitive, and useful metric for determining whether a new energy storage plant would be profitable over its life cycle and to compare the cost of different energy storage technologies. However, researchers and industry decision makers still use conflicting definitions of LCOS. For example, some include charging cost, while others only include round trip efficiency (RTE) losses. Additionally, inputs to the existing formulations are not specific enough to generate repeatable results across studies, which reduces trust in the metric. To push for standardization in economic assessment of batteries and other energy storage devices, the authors review existing definitions of LCOS and identify the desired characteristics for a standard. They then propose a new definition and demonstrate that it fits these characteristics very well relative to other prominent options. Unit analysis is applied to this proposed definition to provide a deeper understanding of the equations and to demonstrate its effectiveness. Finally, the sensitivity of LCOS to different input parameters is investigated to help users understand how to compare analyses from literature to their own. The authors also provide a spreadsheet and a Python script to streamline adoption of the proposed definition.

25 ENERGY STORAGE↗

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $ \$ $6B annually (at $ \$ $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year), and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE) missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

42 ENGINEERING↗

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $6B annually (at $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year),and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE)missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

99 GENERAL AND MISCELLANEOUS↗

Vehicle Integrated Performance Analysis, the VIPA Experience: Reconnecting with Technical Integration

Today's NASA is facing significant challenges and changes. The Exploration initiative indicates a large increase in projects with limited increase in budget. The Columbia report has criticized NASA for its lack of insight and technical integration impacting its ability to provide safety. The Aldridge report is advocating NASA find new ways of doing business. Very early in the Space Launch Initiative (SLI) program a small team of engineers at MSFC were asked to propose a process for performing a system level assessment of a launch vehicle. The request was aimed primarily at providing insight and making NASA a "smart buyer." Out of this effort the VIPA team was created. The difference between the VIPA effort and many integration attempts is that VIPA focuses on using experienced people from various disciplines and a process which focuses them on a technically integrated assessment. Most previous attempts have focused on developing an all encompassing software tool. In addition, VIPA anchored its process formulation in the experience of its members and in early developmental Space Shuttle experience. The primary reference for this is NASA-TP-2001-210092, "Launch Vehicle Design Process: Characterization, Technical Integration, and Lessons Learned," and discussions with its authors. The foundations of VIPA's process are described. The VIPA team also recognized the need to drive detailed analysis earlier in the design process. Analyses and techniques typically done in later design phases, are brought forward using improved computing technology. The intent is to allow the identification of significant sensitivities, trades, and design issues much earlier in the program. This process is driven by the T-model for Technical Integration described in the aforementioned reference. VIPA's approach to performing system level technical integration is discussed in detail. Proposed definitions are offered to clarify this discussion and the general systems integration dialog. VIPA's capabilities and process can now be used to significantly enhance the development and monitoring of realizable project requirements. This is done through the use of VIPA's V-model. Starting with a given concept, VIPA's assessment validates the concept's stated performance, identifies significant issues either with the concept or the requirements, and then re-integrates these issues to determine impacts. This process is discussed along with a description of how it may be integrated into a program's insight and review process. The VIPA process has been employed successfully on several projects including SLI, Orbital Space Plane (OSP), and several heavy lift concepts for Exploration. It has also been proposed for use on the Jupiter Icy Moon (JIMO) spacecraft. The VIPA process has gained favor with both engineering and project organizations for being responsive and insightful. Selected results from these assessments will be presented.

McGhee, David S.↗

Final-state interactions and spin structure in E 1 breakup of Li 11 in halo effective field theory

In this work, we calculate the E1 breakup of the 2n halo nucleus 11 Li in halo effective field theory (Halo EFT) at leading order. In Halo EFT, 11 Li is treated as a three-body system of a 9 Li core and two neutrons. We present a detailed investigation of final-state interactions (FSIs) in the neutron-neutron (nn) and neutron-core (nc) channels. We employ Møller operators to formulate an expansion scheme that satisfies the non-energy-weighted cluster sum rule and successively includes higher-order terms in the multiple-scattering series for the FSI. Computing the E1 strength up to third order in this scheme, we observe apparent convergence and good agreement with experiment. The neutron-neutron FSI is by far the most important contribution and largely determines the maximum value of the E1 distribution. However, inclusion of nc FSI does shift the peak position to slightly lower energies. Moreover, we investigate the sensitivity of the E1 response to the spin structure of the neutron- 9 Li interaction. We contrast results for an interaction that is the same in the spin-1 and spin-2 channels with one that is only operative in the spin-2 channel, and find that good agreement with experimental data is only obtained if the interaction is present in both spin channels. The latter case is shown to be equivalent to a calculation in which the spin of 9 Li is neglected.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Computer modeling of the sensitivity of a laser water vapor sensor to variations in temperature and air speed

Currently, there is disagreement among existing methods of determining atmospheric water vapor concentration at dew-points below -40 C. A major source of error is wall effects which result from the necessity of bringing samples into the instruments. All of these instruments also have response times on the order of seconds. NASA Langley is developing a water vapor sensor which utilizes the absorption of the infrared radiation produced by a diode laser to estimate water vapor concentration. The laser beam is directed through an aircraft window to a retroreflector located on an engine. The reflected beam is detected by an infrared detector located near the laser. To maximize signal to noise, derivative signals are analyzed. By measuring the 2f/DC signal and correcting for ambient temperature, atmospheric pressure and air speed (which results in a Doppler shifting of the laser beam), the water vapor concentration can be retrieved. Since this is an in situ measurement there are no wall effects and measurements can be made at a rate of more than 20 per second. This allows small spatial variations of water vapor to be studied. In order to study the sensitivity of the instrument to variations in temperature and air speed, a computer program which generated the 2f, 3f, 4f, DC and 2f/DC signals of the instrument as a function of temperature, pressure and air speed was written. This model was used to determine the effect of errors in measurement of the temperature and air speed on the measured water vapor concentration. Future studies will quantify the effect of pressure measurement errors, which are expected to be very small. As a result of these studied, a retrieval algorithm has been formulated, and will be applied to data taken during the PEM-West atmospheric science field mission. Spectroscopic studies of the water vapor line used by the instrument will be used to refine this algorithm. To prepare for these studies, several lasers have been studied to determine their output frequency range and power.

Tucker, George F.↗