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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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NASA NTRS1993

Six-degree-of-freedom guidance and control-entry analysis of the HL-20

The ability of the HL-20 lifting body to fly has been evaluated for an automated entry from atmospheric interface to landing. This evaluation was required to demonstrate that not only successful touchdown conditions would be possible for this low lift-to-drag-ratio vehicle, but also the vehicle would not exceed its design dynamic pressure limit of 400 psf during entry. This dynamic pressure constraint limit, coupled with limited available pitch-control authority at low supersonic speeds, restricts the available maneuvering capability for the HL-20 to acquire the runway. One result of this analysis was that this restrictive maneuvering capability does not allow the use of a model-following atmospheric entry-guidance algorithm, such as that used by the Space Shuttle, but instead requires a more adaptable guidance algorithm. Therefore, for this analysis, a predictor-corrector guidance algorithm was developed that would provide successful touchdown conditions while not violating the dynamic pressure constraint. A flight-control system was designed and incorporated, along with the predictor-corrector guidance algorithm, into a six-DOF simulation. which showed that the HL-20 remained controllable and could reach the landing site and execute a successful landing under all off-nominal conditions simulated.

Powell, Richard W.↗
NASA NTRS1994

The Block V Receiver fast acquisition algorithm for the Galileo S-band mission

A fast acquisition algorithm for the Galileo suppressed carrier, subcarrier, and data symbol signals under low data rate, signal-to-noise ratio (SNR) and high carrier phase-noise conditions has been developed. The algorithm employs a two-arm fast Fourier transform (FFT) method utilizing both the in-phase and quadrature-phase channels of the carrier. The use of both channels results in an improved SNR in the FFT acquisition, enabling the use of a shorter FFT period over which the carrier instability is expected to be less significant. The use of a two-arm FFT also enables subcarrier and symbol acquisition before carrier acquisition. With the subcarrier and symbol loops locked first, the carrier can be acquired from an even shorter FFT period. Two-arm tracking loops are employed to lock the subcarrier and symbol loops parameter modification to achieve the final (high) loop SNR in the shortest time possible. The fast acquisition algorithm is implemented in the Block V Receiver (BVR). This article describes the complete algorithm design, the extensive computer simulation work done for verification of the design and the analysis, implementation issues in the BVR, and the acquisition times of the algorithm. In the expected case of the Galileo spacecraft at Jupiter orbit insertion PD/No equals 14.6 dB-Hz, R(sym) equals 16 symbols per sec, and the predicted acquisition time of the algorithm (to attain a 0.2-dB degradation from each loop to the output symbol SNR) is 38 sec.

Aung, M.↗
NASA NTRS2010

Context Modeler for Wavelet Compression of Spectral Hyperspectral Images

A context-modeling sub-algorithm has been developed as part of an algorithm that effects three-dimensional (3D) wavelet-based compression of hyperspectral image data. The context-modeling subalgorithm, hereafter denoted the context modeler, provides estimates of probability distributions of wavelet-transformed data being encoded. These estimates are utilized by an entropy coding subalgorithm that is another major component of the compression algorithm. The estimates make it possible to compress the image data more effectively than would otherwise be possible. The following background discussion is prerequisite to a meaningful summary of the context modeler. This discussion is presented relative to ICER-3D, which is the name attached to a particular compression algorithm and the software that implements it. The ICER-3D software is summarized briefly in the preceding article, ICER-3D Hyperspectral Image Compression Software (NPO-43238). Some aspects of this algorithm were previously described, in a slightly more general context than the ICER-3D software, in "Improving 3D Wavelet-Based Compression of Hyperspectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. In turn, ICER-3D is a product of generalization of ICER, another previously reported algorithm and computer program that can perform both lossless and lossy wavelet-based compression and decompression of gray-scale-image data. In ICER-3D, hyperspectral image data are decomposed using a 3D discrete wavelet transform (DWT). Following wavelet decomposition, mean values are subtracted from spatial planes of spatially low-pass subbands prior to encoding. The resulting data are converted to sign-magnitude form and compressed. In ICER-3D, compression is progressive, in that compressed information is ordered so that as more of the compressed data stream is received, successive reconstructions of the hyperspectral image data are of successively higher overall fidelity.

Kiely, Aaron↗
NASA NTRS2011

Safe Onboard Guidance and Control Under Probabilistic Uncertainty

An algorithm was developed that determines the fuel-optimal spacecraft guidance trajectory that takes into account uncertainty, in order to guarantee that mission safety constraints are satisfied with the required probability. The algorithm uses convex optimization to solve for the optimal trajectory. Convex optimization is amenable to onboard solution due to its excellent convergence properties. The algorithm is novel because, unlike prior approaches, it does not require time-consuming evaluation of multivariate probability densities. Instead, it uses a new mathematical bounding approach to ensure that probability constraints are satisfied, and it is shown that the resulting optimization is convex. Empirical results show that the approach is many orders of magnitude less conservative than existing set conversion techniques, for a small penalty in computation time.

Blackmore, Lars James↗
NASA NTRS2012

Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data

This technique enhances the detection capability of the autonomous Real-Nose system from MIT to detect odorants and their concentrations in noisy and transient environments. The lowcost, portable system with low power consumption will operate at high speed and is suited for unmanned and remotely operated long-life applications. A deterministic mathematical model was developed to detect odorants and calculate their concentration in noisy environments. Real data from MIT's NanoNose was examined, from which a signal conditioning technique was proposed to enable robust odorant detection for the RealNose system. Its sensitivity can reach to sub-part-per-billion (sub-ppb). A Space Invariant Independent Component Analysis (SPICA) algorithm was developed to deal with non-linear mixing that is an over-complete case, and it is used as a preprocessing step to recover the original odorant sources for detection. This approach, combined with the Cascade Error Projection (CEP) Neural Network algorithm, was used to perform odorant identification. Signal conditioning is used to identify potential processing windows to enable robust detection for autonomous systems. So far, the software has been developed and evaluated with current data sets provided by the MIT team. However, continuous data streams are made available where even the occurrence of a new odorant is unannounced and needs to be noticed by the system autonomously before its unambiguous detection. The challenge for the software is to be able to separate the potential valid signal from the odorant and from the noisy transition region when the odorant is just introduced.

Duong, Tuan A.↗
NASA NTRS1996

An Optimal Order Nonnested Mixed Multigrid Method for Generalized Stokes Problems

A multigrid algorithm is developed and analyzed for generalized Stokes problems discretized by various nonnested mixed finite elements within a unified framework. It is abstractly proved by an element-independent analysis that the multigrid algorithm converges with an optimal order if there exists a 'good' prolongation operator. A technique to construct a 'good' prolongation operator for nonnested multilevel finite element spaces is proposed. Its basic idea is to introduce a sequence of auxiliary nested multilevel finite element spaces and define a prolongation operator as a composite operator of two single grid level operators. This makes not only the construction of a prolongation operator much easier (the final explicit forms of such prolongation operators are fairly simple), but the verification of the approximate properties for prolongation operators is also simplified. Finally, as an application, the framework and technique is applied to seven typical nonnested mixed finite elements.

Deng, Qingping↗
NASA NTRS2002

Defect Localization Capabilities of a Global Detection Scheme: Spatial Pattern Recognition Using Full-field Vibration Test Data in Plates

Recently, a conceptually simple approach, based on the notion of defect energy in material space has been developed and extensively studied (from the theoretical and computational standpoints). The present study focuses on its evaluation from the viewpoint of damage localization capabilities in case of two-dimensional plates; i.e., spatial pattern recognition on surfaces. To this end, two different experimental modal test results are utilized; i.e., (1) conventional modal testing using (white noise) excitation and accelerometer-type sensors and (2) pattern recognition using Electronic speckle pattern interferometry (ESPI), a full field method capable of analyzing the mechanical vibration of complex structures. Unlike the conventional modal testing technique (using contacting accelerometers), these emerging ESPI technologies operate in a non-contacting mode, can be used even under hazardous conditions with minimal or no presence of noise and can simultaneously provide measurements for both translations and rotations. Results obtained have clearly demonstrated the robustness and versatility of the global NDE scheme developed. The vectorial character of the indices used, which enabled the extraction of distinct patterns for localizing damages proved very useful. In the context of the targeted pattern recognition paradigm, two algorithms were developed for the interrogation of test measurements; i.e., intensity contour maps for the damaged index, and the associated defect energy vector field plots.

Saleeb, A. F.↗
NASA NTRSDate not supplied

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Preliminary work into this field was promising but given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation (CoCEI) and an execution crowdsourcing platform partner to solicit machine learning framework developments from external contenders. NASA provided contenders with images and video clips of spacesuits with simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, the top five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The weighted scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy. Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA environments such as the NASA Active Response Gravity Offload System (ARGOS). After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗
NASA NTRS1996

Examination of Biomass Fire Temperature and Areal Extent from Calibrated AVIRIS Spectra

Biomass burning is an important process on the Earth at the local, regional and global scales. To investigate issues related to biomass burning, a range of remotely acquired data were measured as part of the NASA Smoke Cloud Aerosol and Radiation experiment in Brazil, 1995. As part of this experiment, images of calibrated spectral radiance from 400 to 2500 nm at 10 nm intervals were acquired by AVIRIS. To investigate the expression of biomass fires in AVIRIS spectra, a model of the upwelling radiance from a burning fire was developed. This spectral model accounts for four components in the 20 by 20 m AVIRIS spatial resolution element. These are: (1) the atmospheric path radiance, (2) the solar reflected radiance from unburnt vegetation and soil, (3) the apparent temperature and area of a primary fire, and (4) the apparent temperature and area of a secondary fire. A nonlinear least squares spectral fitting algorithm was developed to invert this model for the AVIRIS spectra. The derived biomass burning parameters from this algorithm are presented for AVIRIS spectral images acquired over Cuiaba, Brazil on 25 August 1995.

Green Robert O.↗
NASA NTRS1987

Projection filters for modal parameter estimate for flexible structures

Single-mode projection filters are developed for eigensystem parameter estimates from both analytical results and test data. Explicit formulations of these projection filters are derived using the pseudoinverse matrices of the controllability and observability matrices in general use. A global minimum optimization algorithm is developed to update the filter parameters by using interval analysis method. Modal parameters can be attracted and updated in the global sense within a specific region by passing the experimental data through the projection filters. For illustration of this method, a numerical example is shown by using a one-dimensional global optimization algorithm to estimate model frequencies and dampings.

Huang, Jen-Kuang↗
DOE OSTI2025

Graph decomposition techniques for solving combinatorial optimization problems with variational quantum algorithms

The quantum approximate optimization algorithm (QAOA) has the potential to approximately solve complex combinatorial optimization problems in polynomial time. However, current noisy quantum devices cannot solve large problems due to hardware constraints. In this work, we develop an algorithm that decomposes the QAOA input problem graph into a smaller problem and solves MaxCut using QAOA on the reduced graph. The algorithm requires a subroutine that can be classical or quantum—in this work, we implement the algorithm twice on each graph. One implementation uses the classical solver Gurobi in the subroutine and the other uses QAOA. We solve these reduced problems with QAOA. On average, the reduced problems require only approximately 1/10 of the number of vertices than the original MaxCut instances. Furthermore, the average approximation ratio of the original MaxCut problems is 0.75, while the approximation ratios of the decomposed graphs are on average of 0.96 for both Gurobi and QAOA. With this decomposition, we are able to measure optimal solutions for ten 100-vertex graphs by running single-layer QAOA circuits on the Quantinuum trapped-ion quantum computer H1-1, sampling each circuit only 500 times. This approach is best suited for sparse, particularly k-regular graphs, as k-regular graphs on n vertices can be decomposed into a graph with at most $\frac{nk}{k+1}$ vertices in polynomial time. Further reductions can be obtained with a potential trade-off in computational time. In conclusion, while this paper applies the decomposition method to the MaxCut problem, it can be applied to more general classes of combinatorial optimization problems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

Weighted adaptive algorithms for estimation of Gaussian distribution parameters

Two weighted adaptive algorithms are proposed for updating the estimates of the mean vector and the covariance matrix, respectively, in a multispectral pattern recognition system. To achieve computational efficiency, the auxiliary matrices have been utilized in the algorithm for covariance matrix updating. Enhancements in the performance accuracy of a multispectral processing system and extensions of the Gaussian maximum likelihood classification capabilities to larger scale surveys are the motivations in developing the algorithms presented herein.

Chang, C. Y.↗
NASA NTRS1983

Time-critical multirate scheduling using contemporary real-time operating system services

Although real-time operating systems provide many of the task control services necessary to process time-critical applications (i.e., applications with fixed, invariant deadlines), it may still be necessary to provide a scheduling algorithm at a level above the operating system in order to coordinate a set of synchronized, time-critical tasks executing at different cyclic rates. The scheduling requirements for such applications and develops scheduling algorithms using services provided by contemporary real-time operating systems.

Eckhardt, D. E., Jr.↗
NASA NTRS2013

Commercial Non-Dispersive Infrared Spectroscopy Sensors for Sub-Ambient Carbon Dioxide Detection

Carbon dioxide produced through respiration can accumulate rapidly within closed spaces. If not managed, a crew's respiratory rate increases, headaches and hyperventilation occur, vision and hearing are affected, and cognitive abilities decrease. Consequently, development continues on a number of CO2 removal technologies for human spacecraft and spacesuits. Terrestrially, technology development requires precise performance characterization to qualify promising air revitalization equipment. On-orbit, instrumentation is required to identify and eliminate unsafe conditions. This necessitates accurate in situ CO2 detection. Recursive compensation algorithms were developed for sub-ambient detection of CO2 with commercial off-the-shelf (COTS) non-dispersive infrared (NDIR) sensors. In addition, the source of the exponential loss in accuracy is developed theoretically. The basis of the loss can be explained through thermal, Doppler, and Lorentz broadening effects that arise as a result of the temperature, pressure, and composition of the gas mixture under analysis. The objective was to develop a mathematical routine to compensate COTS CO2 sensors relying on NDIR over pressures, temperatures, and compositions far from calibration conditions. The routine relies on a power-law relationship for the pressure dependency of the sensors along with an equivalent pressure to account for the composition dependency. A Newton-Raphson iterative technique solves for actual carbon dioxide concentration based on the reported concentration. Moreover, first principles routines were established to predict mixed-gas spectra based on sensor specifications (e.g., optical path length). The first principles model can be used to parametrically optimize sensors or sensor arrays across a wide variety of pressures/temperatures/ compositions. In this work, heuristic scaling arguments were utilized to develop reasonable compensation techniques. Experimental results confirmed this approach and provided evidence that composition broadening significantly alters spectra when pressure is reduced. Consequently, a recursive compensation technique was developed with the Newton-Raphson method, which was subsequently verified through experimentation.

Swickrath, Michael J.↗
NASA NTRS2015

Estimating Planetary Boundary Layer Heights from NOAA Profiler Network Wind Profiler Data

An algorithm was developed to estimate planetary boundary layer (PBL) heights from hourly archived wind profiler data from the NOAA Profiler Network (NPN) sites located throughout the central United States. Unlike previous studies, the present algorithm has been applied to a long record of publicly available wind profiler signal backscatter data. Under clear conditions, summertime averaged hourly time series of PBL heights compare well with Richardson-number based estimates at the few NPN stations with hourly temperature measurements. Comparisons with clear sky reanalysis based estimates show that the wind profiler PBL heights are lower by approximately 250-500 m. The geographical distribution of daily maximum PBL heights corresponds well with the expected distribution based on patterns of surface temperature and soil moisture. Wind profiler PBL heights were also estimated under mostly cloudy conditions, and are generally higher than both the Richardson number based and reanalysis PBL heights, resulting in a smaller clear-cloudy condition difference. The algorithm presented here was shown to provide a reliable summertime climatology of daytime hourly PBL heights throughout the central United States.

Wind Profiler↗
NASA NTRS2020

Entropy Stable h/p-Nonconforming Discretization with the Summation-by-Parts Property for the Compressible Euler and Navier–Stokes Equations

In this paper, we extend the entropy conservative/stable algorithms presented by Del Rey Fernandez and coauthors for the compressible Euler and Navier-Stokes equations on nonconforming p-refined/coarsened curvilinear grids to h/p refinement/coarsening. The main difficulty in developing nonconforming algorithms is the construction of appropriate coupling procedures across nonconforming interfaces. Here, we utilize a computationally simple and efficient approach based upon using decoupled interpolation operators. The resulting scheme is entropy conservative/stable and elementwise conservative. Numerical simulations of the isentropic vortex and viscous shock propagation con firm the entropy conservation/stability and accuracy properties of the method (achieving ~ p + 1 convergence), which are comparable to those of the original conforming scheme. Simulations of the Taylor{Green vortex at R(e) = 1,600 and turbulent flow past a sphere at R(e(infinity)) = 2,000 show the robustness and stability properties of the overall spatial discretization for unstructured grids. Finally, to demonstrate the entropy conservation property of a fully-discrete explicit entropy stable algorithm with h=p refinement/coarsening, we present the time evolution of the entropy function obtained by simulating the propagation of the isentropic vortex using a relaxation Runge-Kutta scheme.

Nonconforming interfaces↗
DOE OSTI2024

Multistage Stochastic optimization for mid-term integrated generation and maintenance scheduling of cascaded hydroelectric system with renewable energy uncertainty

The uncertainties resulting from the escalating penetration of renewable energy resources pose severe challenges to the efficient operation of modern power systems. Hydroelectricity is characterized by its flexibility, controllability, and reliability, and thus becomes one of the most ideal energy resources to hedge against such uncertainties. This paper studies the mid-term integrated generation and maintenance scheduling of a cascaded hydroelectric system (CHS) consisting of multiple cascaded reservoirs and hydroelectric units. To precisely describe the mid-term water regulation policies, the hydraulic coupling relationship and water-energy nexus of CHS are incorporated into the proposed optimization model. The uncertainties of natural water inflow and the power outputs of wind/solar energy generation are taken into consideration and captured via a stochastic process modeled by a scenario tree. A multistage stochastic optimization (MSO) approach is developed to coordinate the complementary operations of multiple energy resources, by optimizing the mid-term water resource management, generation scheduling, and maintenance scheduling of CHS. The proposed MSO model is formulated as a large-scale mixed-integer linear program that presents significant computational intractability. To address this issue, a tailored Benders decomposition algorithm is developed. Two real-world case studies are conducted to demonstrate the capability and characteristics of the proposed model and algorithm. The computational results show that the proposed MSO model can exploit the flexibility of hydroelectricity to efficiently respond to variable wind and solar power, and reserve water resources for the generation in peak months to reduce the consumption of fossil fuel. Furthermore, the proposed solution approach also exhibits promising computational efficiency when handling large-scale models.

13 HYDRO ENERGY↗
NASA NTRS1987

Computation of diffuse sky irradiance from multidirectional radiance measurements

Accurate determination of the diffuse solar spectral irradiance directly above the land surface is important in characterizing the reflectance properties of these surfaces, especially vegetation canopies. This determination is also needed to infer the net radiation budget of the earth-atmosphere system above these surfaces. An algorithm is developed here for the computation of hemispheric diffuse irradiance using the measurements from an instrument called PARABOLA, which rapidly measures upwelling and downwelling radiances in three selected wavelength bands. The validity of the algorithm is established from simulations. The standard reference data set of diffuse radiances of Dave (1978), obtained by solving the radiative transfer equation numerically for realistic atmospheric models, is used to simulate PARABOLA radiances. Hemispheric diffuse irradiance is estimated from a subset of simulated radiances by using the algorithm described. The algorithm is validated by comparing the estimated diffuse irradiance with the true diffuse irradiance of the standard data set. The validations include sensitivity studies for two wavelength bands (visible, 0.65-0.67 micron; near infrared, 0.81-0.84 micron), different atmospheric conditions, solar elevations, and surface reflectances. In most cases the hemispheric diffuse irradiance computed from simulated PARABOLA radiances and the true irradiance obtained from radiative transfer calculations agree within 1-2 percent. This technique can be applied to other sampling instruments designed to estimate hemispheric diffuse sky irradiance.

Ahmad, Suraiya P.↗