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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4

Algorithm Development for Predicting Biodiversity Based on Phytoplankton Absorption

Ocean color remote sensing has provided the scientific community with unprecedented global coverage of chlorophyll a, an indicator of phytoplankton biomass. Together, satellite-derived chlorophyll a and knowledge of Phytoplankton Functional Types (PFTs) will improve our limited understanding of marine ecosystem responses to physiochemical climate drivers involved in carbon cycle dynamics and linkages. Using cruise data from the Gulf of Maine and the Middle Atlantic Bight (N 269 pairs of HPLC and phytoplankton absorption samples), two modeling approaches were utilized to predict phytoplankton absorption and pigments. Algorithm I predicts the chlorophyll-specific absorption coefficient (a*(sub ph) (m(exp 2) mg chl a(exp - 1)) using inputs of temperature, light, and chlorophyll a. Modeled r(exp 2) values (400700 nm) ranged from 0.79 to 0.99 when compared to in situ observations with approximately 25 percent lower r(exp 2) values in the UV region. Algorithm II-a utilizes matrix inversion analysis to predict a(sub ph)(m(exp -1), 400700 nm) and r(exp 2) values ranged from 0.89 to 0.99. The prediction of phytoplankton pigments with Algorithm II-b produced r(exp 2) values that ranged from 0.40 to 0.93. When used in combination, Algorithm I, and Algorithm II-a are able to use satellite products of SST, PAR, and chlorophyll a (Algorithm I) to predict pigment concentrations and ratios to describe the phytoplankton community. The results of this study demonstrate that the spatial variation in modeled pigment ratios differ significantly from the 10-year SeaWiFS average chlorophyll a data set. Contiguous observations of chlorophyll a and phytoplankton biodiversity will elucidate ecosystem responses with unprecedented complexity.

phytoplankton↗

Overview of the Dragonfly Entry Aerosciences Measurements (DrEAM) Suite

NASA Ames and Langley arepartnering with DLR to propose acomprehensive instrumentation suite known as the Dragonfly Entry Aerosciences Meas-urements (DrEAM). DrEAM being the first competed mission to fly EDL instrumentation as part of NASA’s Engineering Science Investigation (ESI).DrEAM will provide key aerothermodynamicdata and performance analysisfor Dragonfly’s forebody and backshell therma lprotection system (TPS),and also includes a DLR-provided Data Acquisition System(DAS).Titan’s atmosphere predominantly consists of nitro-gen (~98% by mole) with small amounts of methane(~2% by mole)and other trace gases. CN is a strong ra-diator and is found in nonequilibriumconcentrationsfor Titan entry. The accurate modeling of nonequilibrium CN radiation has proven to be a difficult task. Prompted by the Huygensmission, many experimental campaigns and analyses were performed to better understand the aerothermal environments experience by the probe dur-ing Titan entry[1].However, the Huygens probe carried no heatshieldinstrumentation. Therefore,the DrEAM instrumentation suite will significantly advance the state-of-the-art not only by documenting theenviron-ment and performance of Dragonfly’sentry system but also by making keymeasurements in Titan’s atmos-phere for thefirst time, thus providing new benchmark dataapplicable to entry science more generally. Current Measurement Goals: Aerothermal envi-ronments and TPS responsewill be measured using sen-sors similarto the Mars Entry, Descent, and Landing In-strumentation2 (MEDLI2) Integrated Sensor Plug(MISP) and the COMbined Aerothermaland Radiome-ter Sensor (COMARS)suite[2], with the latter supplied by DLR.For MEDLI2, MISP usedembedded thermo-couples (TCs) todirectly measure in-depth temperature of theTPS at several locations,which can also be used to infer surface environmentsvia inverse analysis. For DrEAM, the MISPstyle plugswill be known as Drag-onfly Sensors for Aero-Thermal Reconstruction (Drag-STR)plugs. On Schiaparelli, the COMARSsuite in-cludedthree total surface-mounted heatflux sensors, three pressure sensors, and one radiometer. For DrEAM, the COMARS package will be known as COmbined Sensor System for Titan Atmosphere (COSSTA). Atmospheric density measurements and capsuleaerodynamic data will be obtained throughthe onboard Inertial Measurement Unit (IMU),supple-mented by pressure transducers similar tothose used by the MEDLI Mars Entry AtmosphericData System (MEADS).The DrEAM pressure sensors will be known as Dragonfly Atmospheric Flight Transducers(DrAFT) Both DragSTR and DrAFThave flight heritagefrom MISP and MEADS on the MSLand Mars 2020mis-sions, and the COMARS suite successfullyflew on the ESA Schiaparelli EDMlander. A preliminary layout of the sensors is shown in Fig. 1. Because Dragonflyuses the same aeroshell provider (i.e., LockheedMartin) and materials for the TPS,with what are expected to be sim-ilar thicknesses as MSL and Mars 2020on both the heat shield and backshell, theDrEAMinstrumentation will look to utilize the same techniques and processes as de-veloped byMEDLI and MEDLI2for vehicle integra-tion. This commonality alsoenables DrEAMto lever-age the extensiveground test qualifications performed forMEDLI and MEDLI2 and claim substantial heritagefor this system.

A Brandis↗

Damage Detection of a Pressure Vessel with Smart Sensing and Deep Learning

Structural Health Monitoring plays a crucial role in ensuring the safety and reliability of critical infrastructure, including pressure vessels involved in various applications. This research reports the damage detection of a pressure box employed in space habitat that operates in harsh environment where both structural failure and bolt joint loosening may occur. These failure modes are extremely hard to model based on first principles. We explore proper sensing mechanism and the associated inverse analysis algorithm that can elucidate the health condition of the pressure box. It is identified that piezoelectric impedance based active interrogation can provide necessary information for damage detection in such a system. Concurrently, deep learning technique leveraging spatial convolutional neural network is synthesized to analyze the raw data acquired and identify different types of damage. By training the deep learning model on a dataset of healthy and various damage scenarios, we can achieve high accuracy in identifying the presence of damage and its type. This research provides a data-driven methodology for structural damage detection using deep learning and has the potential to be extended to various systems with different failure modes.

Yang Zhang↗

Development of direct-inverse 3-D methods for applied aerodynamic design and analysis

Several inverse methods have been compared and initial results indicate that differences in results are primarily due to coordinate systems and fuselage representations and not to design procedures. Further, results from a direct-inverse method that includes 3-D wing boundary layer effects, wake curvature, and wake displacement are presented. These results show that boundary layer displacements must be included in the design process for accurate results.

Carlson, Leland A.↗

Implementation and (Inverse Modified) Error Analysis for Implicitly Templated ODE-Nets

We focus on learning unknown dynamics from data using ODE-nets templated on implicit numerical initial value problem solvers. First, we perform inverse modified error analysis of the ODE-nets using unrolled implicit schemes for ease of interpretation. It is shown that training an ODE-net using an unrolled implicit scheme returns a close approximation of an inverse modified differential equation (IMDE). In addition, we establish a theoretical basis for hyperparameter selection when training such ODE-nets, whereas current strategies usually treat numerical integration of ODE-nets as a black box. We thus formulate an adaptive algorithm which monitors the level of error and adapts the number of (unrolled) implicit solution iterations during the training process, so that the error of the unrolled approximation is less than the current learning loss. This helps accelerate training while maintaining accuracy. Several numerical experiments are performed to demonstrate the advantages of the proposed algorithm compared to nonadaptive unrollings and validate the theoretical analysis. Here, we also note that this approach naturally allows for incorporating partially known physical terms in the equations, giving rise to what is termed “gray box” identification.

ODE-nets↗

Development of direct-inverse 3-D methods for applied transonic aerodynamic wing design and analysis

An inverse wing design method was developed around an existing transonic wing analysis code. The original analysis code, TAWFIVE, has as its core the numerical potential flow solver, FLO30, developed by Jameson and Caughey. Features of the analysis code include a finite-volume formulation; wing and fuselage fitted, curvilinear grid mesh; and a viscous boundary layer correction that also accounts for viscous wake thickness and curvature. The development of the inverse methods as an extension of previous methods existing for design in Cartesian coordinates is presented. Results are shown for inviscid wing design cases in super-critical flow regimes. The test cases selected also demonstrate the versatility of the design method in designing an entire wing or discontinuous sections of a wing.

Carlson, Leland A.↗

The engine design engine. A clustered computer platform for the aerodynamic inverse design and analysis of a full engine

An application for parallel computation on a combined cluster of powerful workstations and supercomputers was developed. A Parallel Virtual Machine (PVM) is used as message passage language on a macro-tasking parallelization of the Aerodynamic Inverse Design and Analysis for a Full Engine computer code. The heterogeneous nature of the cluster is perfectly handled by the controlling host machine. Communication is established via Ethernet with the TCP/IP protocol over an open network. A reasonable overhead is imposed for internode communication, rendering an efficient utilization of the engaged processors. Perhaps one of the most interesting features of the system is its versatile nature, that permits the usage of the computational resources available that are experiencing less use at a given point in time.

Sanz, J.↗

DNA Sequence Analysis of an Inversion Hot Spot in Lobeliaceae Plastomes

The evolution of plastid genomes (plastomes) in land plants is typically conservative, with extensive structural rearrangements present in only a few groups. Early Southern blot analysis identified two Lobelia species that minimally required deletion of the plastid gene accD and five inversions to account for their plastome arrangement relative to the ancestral organization. Sixty alternative 5-step inversion scenarios could account for the observed arrangement, but only one scenario was consistent with the criterion of ‘common cause’ attributable to a putative rearrangement hot spot at the accD deletion-site. Plastome sequencing demonstrated that this previously hypothesized inversion order is historically accurate. Detailed reconstructions of the ancestral plastome organization before and after each inversion are presented herein. Stem-loop and disruption-rescue models were evaluated for each inversion. One inversion has an obvious stem-loop basis, but the other four inversions were primarily caused by serial insertion of foreign (extra-plastid) DNA bearing large open-reading frames that disrupted plastome organization at the accD deletion-site, and complete plastomes were rescued by seemingly arbitrary ligation or fortuitous recombination at the other inversion endpoint. Transposed copies of DNA segments from elsewhere in the plastome are frequently inserted at inversion junctions, and four junctions are consistent with the stem-loop ligation model.

59 BASIC BIOLOGICAL SCIENCES↗

Application of direct-inverse techniques to airfoil analysis and design

The direct-inverse technique was developed into a numerical method, called TRANDES, that is suitable for the analysis and design of subsonic and transonic airfoils and for the evaluation of design concepts. A general description of the method is given and its application to a design analysis type of problem is demonstrated. A usage of the method for the low speed high lift case is discussed.

Carlson, L. A.↗

The GLAS physical inversion method for analysis of TIROS N data

The Goddard Laboratory for Atmospheric Sciences approach to temperature sounding from satellite observations is fundamentally different from that of NESS in that heavy reliance is placed on the ability to model accurately the instrumental response to atmospheric and surface conditions, while no use is made of statistical relationships between satellite observations and atmospheric temperature profiles. The method involves starting with a guess set of atmospheric and surface conditions from which expected brightness temperatures for the satellite observations are computed. Then, iterative relaxation of atmospheric and surface conditions is performed according to the difference between observed and computed brightness temperatures until sufficient agreement is reached. In the absence of sufficient agreement, no retrieval is produced for that location.

Susskind, J.↗

Analysis of the inversion monitoring capabilities of a monostatic acoustic radar in complex terrain

A qualitative interpretation of the records from a monostatic acoustic radar is presented. This is achieved with the aid of airplane, helicopter, and rawinsonde temperature soundings. The diurnal structure of a mountain valley circulation pattern is studied with the use of two acoustic radars, one located in the valley and one on the downwind ridge. The monostatic acoustic radar was found to be sufficiently accurate in locating the heights of the inversions and the mixed layer depth to warrant use by industry even in complex terrain.

Koepf, D.↗

The GLAS physical inversion method for analysis of HIRS2/MSU sounding data

Goddard Laboratory for Atmospheric Sciences has developed a method to derive atmospheric temperature profiles, sea or land surface temperatures, sea ice extent and snow cover, and cloud heights and fractional cloud, from HIRS2/MSU radiance data. Chapter 1 describes the physics used in the radiative transfer calculations and demonstrates the accuracy of the calculations. Chapter 2 describes the rapid transmittance algorithm used and demonstrates its accuracy. Chapter 3 describes the theory and application of the techniques used to analyze the satellite data. Chapter 4 shows results obtained for January 1979.

Susskind, J.↗

Inverse heat transfer analysis of Bridgman crystal growth

The effects of asymmetry in furnace temperature profile and pulling velocity on the crystal interface shape are demonstrated while neglecting the latent heat of solidification. It is seen that the furnace temperature profile may be varied in order to influence the shape of the melt-crystal interface. An exact thermal analysis is then performed on the Bridgman technique by including the latent heat of solidification as a source term. The exact temperature field required for yielding a flat melt-crystal interface is obtained. The earlier observation regarding the influence of furnace temperature profile on the interface shape is confirmed and a criterion for achieving a flat interface is obtained. Various furnace temperature profiles are selected and their corresponding melt-crystal interface results are presented.

Taghavi, K.↗

Aerodynamic inverse design and analysis for a full engine

A numerical design methodology for multistage turbomachinery is being developed that minimizes the use of experimental data required in the design process. This approach is resulting in an efficient method of enlarging the design database for turbomachinery blading. This capability has been demonstrated for blade sections, and the goal is to extend it to fully three dimensional, multistage configurations.

Sanz, Jose M.↗