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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Low Cost Rapid Response Spacecraft, (LCRRS): A Research Project in Low Cost Spacecraft Design and Fabrication in a Rapid Prototyping Environment

The Low Cost Rapid Response Spacecraft (LCRRS) is an ongoing research development project at NASA Ames Research Center (ARC), Moffett Field, California. The prototype spacecraft, called Cost Optimized Test for Spacecraft Avionics and Technologies (COTSAT) is the first of what could potentially be a series of rapidly produced low-cost satellites. COTSAT has a target launch date of March 2009 on a SpaceX Falcon 9 launch vehicle. The LCRRS research system design incorporates use of COTS (Commercial Off The Shelf), MOTS (Modified Off The Shelf), and GOTS (Government Off The Shelf) hardware for a remote sensing satellite. The design concept was baselined to support a 0.5 meter Ritchey-Chretien telescope payload. This telescope and camera system is expected to achieve 1.5 meter/pixel resolution. The COTSAT team is investigating the possibility of building a fully functional spacecraft for $500,000 parts and $2,000,000 labor. Cost is dramatically reduced by using a sealed container, housing the bus and payload subsystems. Some electrical and RF designs were improved/upgraded from GeneSat-1 heritage systems. The project began in January 2007 and has yielded two functional test platforms. It is expected that a flight-qualified unit will be finished in December 2008. Flight quality controls are in place on the parts and materials used in this development with the aim of using them to finish a proto-flight satellite. For LEO missions the team is targeting a mission class requiring a minimum of six months lifetime or more. The system architecture incorporates several design features required by high reliability missions. This allows for a true skunk works environment to rapidly progress toward a flight design. Engineering and fabrication is primarily done in-house at NASA Ames with flight certifications on materials. The team currently employs seven Full Time Equivalent employees. The success of COTSATs small team in this effort can be attributed to highly cross trained engineering team. The engineers on the team are capable of functioning in two to three engineering disciplines which allows highly efficient interdisciplinary engineering collaboration. NASA Ames is actively proposing mission concepts to use the COTSAT platform to accomplish science. If the COTSAT team validates this approach, it will allow the possibility for remote sensing missions to produce a high science yield for minimal cost and reduced schedule. Another aim of this approach is to yield an accelerated pathway from a Phase A study to mission launch. Leaders in the aerospace industry have shown interest in this methodology. Several visits and tours have been given in the lab. Although the concept of low-cost development is initially met with skepticism from some within the prohibitive aerospace industry, the project's efforts have been highly praised for the accomplishments met within a limited time and budget. Overall the development has progressed tremendously well and the team is answering critical questions for current and future low-cost small satellite developments. COTSAT subsystems are not limited to a specific weight class and could be adapted to produce smaller platforms and to fit various launch vehicles.

Spremo, Stevan↗
NASA NTRS2010

Exploring Discretization Error in Simulation-Based Aerodynamic Databases

This work examines the level of discretization error in simulation-based aerodynamic databases and introduces strategies for error control. Simulations are performed using a parallel, multi-level Euler solver on embedded-boundary Cartesian meshes. Discretization errors in user-selected outputs are estimated using the method of adjoint-weighted residuals and we use adaptive mesh refinement to reduce these errors to specified tolerances. Using this framework, we examine the behavior of discretization error throughout a token database computed for a NACA 0012 airfoil consisting of 120 cases. We compare the cost and accuracy of two approaches for aerodynamic database generation. In the first approach, mesh adaptation is used to compute all cases in the database to a prescribed level of accuracy. The second approach conducts all simulations using the same computational mesh without adaptation. We quantitatively assess the error landscape and computational costs in both databases. This investigation highlights sensitivities of the database under a variety of conditions. The presence of transonic shocks or the stiffness in the governing equations near the incompressible limit are shown to dramatically increase discretization error requiring additional mesh resolution to control. Results show that such pathologies lead to error levels that vary by over factor of 40 when using a fixed mesh throughout the database. Alternatively, controlling this sensitivity through mesh adaptation leads to mesh sizes which span two orders of magnitude. We propose strategies to minimize simulation cost in sensitive regions and discuss the role of error-estimation in database quality.

Aftosmis, Michael J.↗
NASA NTRS2012

System and method for cognitive processing for data fusion

A system and method for cognitive processing of sensor data. A processor array receiving analog sensor data and having programmable interconnects, multiplication weights, and filters provides for adaptive learning in real-time. A static random access memory contains the programmable data for the processor array and the stored data is modified to provide for adaptive learning.

Duong, Tuan A.↗
DOE OSTI2026

LAF-Net: A Deep Residual and Cross-Attention Framework for Day-Ahead Load Forecasting: Preprint

Accurate day-ahead load forecasting is essential for reliable power system operations and market efficiency. System operators such as the Midcontinent Independent System Operator (MISO) rely on forecasts from multiple vendors, yet combining them effectively remains a persistent challenge due to vendor-specific biases. This paper presents a novel LSTM-Attention Fusion Network with Error Representation (LAF-Net) that enhances day-ahead hourly load forecasting through deep residual learning and multi-modal cross-attention. The proposed model builds a historical error memory from past vendor performance and dynamically queries it with future hour context to generate adaptive, hour-specific trust weights for each vendor. A bounded residual correction further refines forecasts by mitigating systematic and temporally localized errors. Tested on real MISO LBA data with multi-vendor forecasts, LAF-Net consistently outperforms the best vendor baseline across all 38 LBAs, achieving more than a 40% reduction in system-level mean absolute error (MAE) during peak load hours relative to the best vendor baseline.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Data-Driven Forgetting and Discount Factors for Vehicle Speed Forecasting in Ecological Adaptive Cruise Control

Abstract This paper investigates temporal correlations in human driving behavior using real-world driving to improve speed forecasting accuracy. These correlations can point to a measurement weighting function with two parameters: a forgetting factor for past speed measurements that the vehicle itself drove with, and a discount factor for the speeds of vehicles ahead based on information from vehicle-to-vehicle communication. The developed weighting approach is applied to a vehicle speed predictor using polynomial regression, a prediction method well-known in the literature. The performance of the developed approach is then assessed in both real-world and simulated traffic scenarios for accuracy and robustness. The new weighting method is applied to an ecological adaptive cruise control system, and its influence is analyzed on the prediction accuracy and the performance of the ecological adaptive cruise control in an electric vehicle powertrain model. The results show that the new prediction method improves energy saving from the eco-driving by up to 4.7% compared to a baseline least-square-based polynomial regression. This is a 10% improvement over the constant speed/acceleration model, a conventional speed predictor.

Automation & Control Systems↗
NASA NTRS1993

Adaptive array antenna for satellite cellular and direct broadcast communications

Adaptive phased-array antennas provide cost-effective implementation of large, light weight apertures with high directivity and precise beamshape control. Adaptive self-calibration allows for relaxation of all mechanical tolerances across the aperture and electrical component tolerances, providing high performance with a low-cost, lightweight array, even in the presence of large physical distortions. Beam-shape is programmable and adaptable to changes in technical and operational requirements. Adaptive digital beam-forming eliminates uplink contention by allowing a single electronically steerable antenna to service a large number of receivers with beams which adaptively focus on one source while eliminating interference from others. A large, adaptively calibrated and fully programmable aperture can also provide precise beam shape control for power-efficient direct broadcast from space. Advanced adaptive digital beamforming technologies are described for: (1) electronic compensation of aperture distortion, (2) multiple receiver adaptive space-time processing, and (3) downlink beam-shape control. Cost considerations for space-based array applications are also discussed.

Horton, Charles R.↗
NASA NTRS1977

Structured estimation - Sample size reduction for adaptive pattern classification

The Gaussian two-category classification problem with known category mean value vectors and identical but unknown category covariance matrices is considered. The weight vector depends on the unknown common covariance matrix, so the procedure is to estimate the covariance matrix in order to obtain an estimate of the optimum weight vector. The measure of performance for the adapted classifier is the output signal-to-interference noise ratio (SIR). A simple approximation for the expected SIR is gained by using the general sample covariance matrix estimator; this performance is both signal and true covariance matrix independent. An approximation is also found for the expected SIR obtained by using a Toeplitz form covariance matrix estimator; this performance is found to be dependent on both the signal and the true covariance matrix.

Morgera, S.↗
DOE OSTI2023

High-Order Mesh Morphing for Boundary and Interface Fitting to Implicit Geometries

Here, we propose a method that morphs high-order meshes such that their boundaries and interfaces coincide/align with implicitly defined geometries. Our focus is particularly on the case when the target surface is prescribed as the zero isocontour of a smooth discrete function. Common examples of this scenario include using level set functions to represent material interfaces in multimaterial configurations, and evolving geometries in shape and topology optimization. The proposed method formulates the mesh optimization problem as a variational minimization of the sum of a chosen mesh-quality metric using the Target-Matrix Optimization Paradigm (TMOP) and a penalty term that weakly forces the selected faces of the mesh to align with the target surface. The distinct features of the method are use of a source mesh to represent the level set function with sufficient accuracy, and adaptive strategies for setting the penalization weight and selecting the faces of the mesh to be fit to the target isocontour of the level set field. We demonstrate that the proposed method is robust for generating boundary- and interface-fitted meshes for curvilinear domains using different element types in 2D and 3D.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

Ground Reaction Force and Mechanical Differences Between the Interim Resistive Exercise Device (iRED) and Smith Machine While Performing a Squat

Musculoskeletal unloading in microgravity has been shown to induce losses in bone mineral density, muscle cross-sectional area, and muscle strength. Currently, an Interim Resistive Exercise Device (iRED) is being flown on board the ISS to help counteract these losses. Free weight training has shown successful positive musculoskeletal adaptations. In biomechanical research, ground reaction forces (GRF) trajectories are used to define differences between exercise devices. The purpose of this evaluation is to quantify the differences in GRF between the iRED and free weight exercise performed on a Smith machine during a squat. Due to the differences in resistance properties, inertial loading and load application to the body between the two devices, we hypothesize that subjects using iRED will produce GRF that are significantly different from the Smith machine. There will be differences in bar/harness range of motion and the time when peak GRF occurred in the ROMbar. Three male subjects performed three sets of ten squats on the iRED and on the Smith Machine on two separate days at a 2-second cadence. Statistically significant differences were found between the two devices in all measured GRF variables. Average Fz and Fx during the Smith machine squat were significantly higher than iRED. Average Fy (16.82 plus or minus.23; p less than .043) was significantly lower during the Smith machine squat. The mean descent/ascent ratio of the magnitude of the resultant force vector of all three axes for the Smith machine and iRED was 0.95 and 0.72, respectively. Also, the point at which maximum Fz occurred in the range of motion (Dzpeak) was at different locations with the two devices.

Amonette, William E.↗
DOE OSTI2019

Efficient Multiscale Optoelectronic Prediction for Conjugated Polymers

Conjugated polymers represent a high-potential material class due to the tunability of their optoelectronic properties via straightforward processing protocols. However, to in silico tailor these optoelectronic properties, one must compute the conformationally dependent electronic structure over mesoscopic length and time scales. This task represents a challenging multiscale computational problem in which quantum chemistry and atomistic or coarse-grained molecular dynamics must be integrated. Recently, we introduced a methodology, called electronic coarse graining (ECG), that utilizes artificial neural networks to compute ab initio quality electronic structures using only the reduced degrees of freedom of coarse-grained models. Here, we adapt ECG to variable-molecular weight conjugated oligomers by casting the problem in the framework of sequence detection. A machine-learning (ML) architecture employing one-dimensional convolutional neural networks and long short-term memory networks is utilized to compute ground-state orbital energies, charge density distributions, and optical spectra solely from the coarse-grained model's configurational degrees of freedom. Robust molecular weight transferability for ECG is established via a A-ML approach that leverages model electronic Hamiltonians for ground and excited-state property determination. The accuracy and transferability of the ECG methodology opens the door for scalable optoelectronic property prediction in conjugated polymers directly from coarse-grained degrees of freedom.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scaling Out a Combinatorial Algorithm for Discovering Carcinogenic Gene Combinations to Thousands of GPUs

Cancer is a leading cause of death in the US, second only to heart disease. It is primarily a result of a combination of an estimated two-nine genetic mutations (multi-hit combinations). Although a body of research has identified hundreds of cancer-causing genetic mutations, we don’t know the specific combination of mutations responsible for specific instances of cancer for most cancer types. An approximate algorithm for solving the weighted set cover problem was previously adapted to identify combinations of genes with mutations that may be responsible for individual instances of cancer. However, the algorithm’s computational requirement scales exponentially with the number of genes, making it impractical for identifying more than three-hit combinations, even after the algorithm was parallelized and scaled up to a V100 GPU. Since most cancers have been estimated to require more than three hits, we scaled out the algorithm to identify combinations of four or more hits using 1000 nodes (6000 V100 GPUs with ≈48×106 processing cores) on the Summit supercomputer at Oak Ridge National Laboratory. Efficiently scaling out the algorithm required a series of algorithmic innovations and optimizations for balancing an exponentially divergent workload across processors and for minimizing memory latency and inter-node communication. We achieved an average strong scaling efficiency of 90.14% (80.96%–97.96% for 200 to 1000 nodes), compared to a 100 node run, with 84.18% scaling efficiency for 1000 nodes. With experimental validation, the multi-hit combinations identified here could provide further insight into the etiology of different cancer subtypes and provide a rational basis for targeted combination therapy.

Dash, Sajal↗
NASA NTRS1973

Weightlessness

Weightlessness effects on physiological systems are summarized, including cardiovascular responses, hematological effects, work capacity (exercise tolerance), respiratory responses, skeletal responses, neuromuscular changes, vestibular responses, metabolism, endocrine and electrolyte responses, and weight loss. The nature of the adaptive response to space flight and microbial changes are also discussed. The effects of zero gravity upon performance are ascertained, and the physiological effects of weightlessness are counteracted.

Charles Berry↗
NASA NTRS1994

Cheaper Synthesis Of Multipole-Brushless-dc-Motor Current

Circuit converts output of single two-phase shaft-angle resolver to that of multi-speed three-phase shaft-angle resolver. Converter circuit applicable to generation of multispeed, multiphase shaft-angle-resolver signals from single two-phase shaft-angle resolver. Combination of converter circuit and single two-phase shaft-angle resolver offer advantages in cost, weight, size, and complexity. Design readily adaptable to two-phase motor.

Alhorn, Dean C.↗
NASA NTRS1996

Optimal Design of Grid-Stiffened Composite Panels Using Global and Local Buckling Analysis

A design strategy for optimal design of composite grid-stiffened panels subjected to global and local buckling constraints is developed using a discrete optimizer. An improved smeared stiffener theory is used for the global buckling analysis. Local buckling of skin segments is assessed using a Rayleigh-Ritz method that accounts for material anisotropy and transverse shear flexibility. The local buckling of stiffener segments is also assessed. Design variables are the axial and transverse stiffener spacing, stiffener height and thickness, skin laminate, and stiffening configuration. The design optimization process is adapted to identify the lightest-weight stiffening configuration and pattern for grid stiffened composite panels given the overall panel dimensions, design in-plane loads, material properties, and boundary conditions of the grid-stiffened panel.

Ambur, Damodar R.↗
NASA NTRS2001

Optimal Design of Grid-Stiffened Panels and Shells With Variable Curvature

A design strategy for optimal design of composite grid-stiffened structures with variable curvature subjected to global and local buckling constraints is developed using a discrete optimizer. An improved smeared stiffener theory is used for the global buckling analysis. Local buckling of skin segments is assessed using a Rayleigh-Ritz method that accounts for material anisotropy and transverse shear flexibility. The local buckling of stiffener segments is also assessed. Design variables are the axial and transverse stiffener spacing, stiffener height and thickness, skin laminate, and stiffening configuration. Stiffening configuration is herein defined as a design variable that indicates the combination of axial, transverse and diagonal stiffeners in the stiffened panel. The design optimization process is adapted to identify the lightest-weight stiffening configuration and stiffener spacing for grid-stiffened composite panels given the overall panel dimensions. in-plane design loads, material properties. and boundary conditions of the grid-stiffened panel or shell.

Ambur, Damodar R.↗
NASA NTRS2001

Effects of chair restraint on the strength of the tibia in rhesus monkeys

To determine the effects of the relative inactivity and unloading on the strength of the tibias of monkeys, Macaca mulatta, we used a non-invasive test to measure bending stiffness, or EI (Nm2), a mechanical property. The technique was validated by comparisons of in vivo measurements with standard measures of EI in the same bones post-mortem (r2 = 0.95, P < 0.0001). Inter-test precision was 4.28+/-1.4%. Normative data in 24 monkeys, 3.0+/-0.7 years and 3.6+/-0.6 kg, revealed EI to be 16% higher in the right than left tibia (4.4+/-1.6 vs. 3.7+/-1.6 Nm2, P < 0.05). Five monkeys, restrained in chairs for 14 days, showed decreases in EI. There were no changes in EI in two chaired monkeys that lost weight during a 2-week space flight. The factors that account for both the decreases in bone mechanical properties after chair restraint at 1 g and lack of change after microgravity remain to be identified. Metabolic factors associated with body weight changes are suggested by our results.

NASA Discipline Musculoskeletal↗
DOE OSTI2025

Wellbore Stability and Mud Loss Management in Geothermal Drilling: Optimizing Mud Weight to Mitigate Tensile Wellbore Fracturing at The Geysers, California

As part of a U.S. Department of Energy (DOE) Geothermal Technologies Office-funded initiative, Geysers Power Company, LLC, a subsidiary of Calpine Corporation, has been working to enhance drilling performance at the world’s largest geothermal field, The Geysers, in northern California. In a recent drilling operation of the GDC-36 well, excessive mud losses were encountered, initially addressed through repeated but largely ineffective cement plugging. Ultimately, the most effective strategy was to drill blind through the loss zones, made feasible by the high rate of penetration (ROP) achieved with PDC bits, allowing significant progress before the mud tanks were depleted and water-sensitive argillic formation layers could collapse. In response to these challenges, the project team explored alternative methods to minimize downtime and risks associated with cement plugging and continuous mud loss and to contemplate the driving mechanisms for the losses. Wellbore imaging using Formation MicroImager (FMI) and Ultrasonic Borehole Imager (UBI) tools revealed longitudinal tensile fractures, which were attributed to mud weights exceeding the minimum circumferential stress resulting from the native stress field and formation pressure. This study examines the mud losses encountered and leverages wellbore imaging data to understand the mechanisms behind mud induced tensile fracturing in specific rock facies. Understanding fracture behavior across different lithologies is crucial, as fractures within the reservoir can enhance steam migration throughout the system. The reservoir at The Geysers lies within the Mesozoic Franciscan Assemblage, a tectonic mélange formed by subduction. It consists of metamorphosed turbidite sandstone (greywacke) and mudstone (argillite), oceanic upper crust (including greenstone and chert), and serpentinized ultramafic rocks - each exhibiting distinct geomechanical fracturing properties. The structural fabric of the Franciscan Assemblage was shaped by low-angle Mesozoic thrust faulting and later overprinted by sub-vertical strike-slip structures related to the Pacific-North American plate boundary. A wellbore stability model was developed using core measurements and logs to simulate fracturing scenarios during drilling under varying stress conditions. These simulations guided the development of an optimized mud weight management strategy that should enable adaptive adjustments during drilling, reducing the likelihood of tensile fracturing and mud losses, ultimately improving operational efficiency.

15 GEOTHERMAL ENERGY↗
NASA NTRS1980

Catecholamines of the adrenal medula and their morphological changes during adaptation to repeated immobilization stress

Changes of the adrenal medulla of rats were studied in the course of adaptation to repeated immobilization stress. An increase in the number of cells in the adrenal medulla was found in the adapted animals; this increase was confirmed by weight indices of the medulla and by cell counts per surface unit. Simultaneous karyometric measurements of the nuclei of adrenal medulla cells and an analysis of the catecholamine contents in the adrenals explain the increased activity of the adrenal medulla in the course of adaptation.

Kvetnansky, R.↗