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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Trajectory Generation for Noise-Constrained Autonomous Flight Operations

One of the major factors in acceptance of aircraft operating in urban areas is noise. In this work, we build on a framework for trajectory generation in order to account for limits on acousticmetrics at one ormore observer locations. The spatial trajectories are generated using Bézier polynomials and satisfy dynamic, acoustic, and mission constraints. The trajectories also guarantee spatial or temporal separation between vehicles for multi-vehicle operations. A simulation example is provided that demonstrates the reduction in noise levels at a set of measurement locations.

Ackerman, Kasey A.↗
DOE OSTI2023

Optimized self-designing key-value storage engine

Embodiments of the invention utilize an optimized key-value storage engine to strike the optimal balance between cloud-cost and performance and supports queries, including updates, lookups, range queries, inserts, and read-modify-writes. Cloud cost is manifested in purchasing both storage and processing resources. The improved approach has the ability to self-design and instantiate holistic configurations given a workload, a cloud budget, and optionally performance goals and a set of Service Level Agreement (SLA) specifications. A configuration reflects an optimized storage engine design in terms of, for example, the individual data structures design (in-memory and on-disk) in the engine as well as their algorithms and interactions, a cloud provider, and the exact virtual machines to be used.

Idreos, Stratos↗
DOE OSTI2025

KIPM Detector Characterization in QUIET

Kinetic Inductance Phonon‑Mediated (KIPM) detectors are superconducting microwave resonators that sense energy depositions in the substrate through a transient shift in their resonant frequency. In this work, I installed new devices in the QUIET cryogenic facility and used a network analyzer to drive them across a range of power levels. At each setting, I measured the transmitted signal and fit it to a simple notch‑filter model, allowing us to extract key performance metrics. Despite the increased noise at low power, the model consistently captured the resonance behavior. I first measured the resonance parameters as a function of RF drive power, then repeated the measurement across a range of temperatures to test whether the device behaved like an MKID. While the notch-filter fits captured the resonance reliably, the observed temperature dependence did not match the expected MKID signature — indicating that these first in-house fabricated chips are not yet functioning as true MKIDs. Overall, this reframes our work as a study of resonance parameter extraction and identification, pointing towards future iterations of device design and fabrication to get the true MKID response.

Savitala, Akash [U. Washington, Seattle (main); Fe↗
NASA NTRS1990

Extensions of algebraic image operators: An approach to model-based vision

Researchers extend their previous research on a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets. Addition and multiplication are defined for the set of all grey-level images, which can then be described as polynomials of two variables. Utilizing this new algebraic structure, researchers devised an innovative, efficient edge detection scheme. An accurate method for deriving gradient component information from this edge detector is presented. Based upon this new edge detection system researchers developed a robust method for linear feature extraction by combining the techniques of a Hough transform and a line follower. The major advantage of this feature extractor is its general, object-independent nature. Target attributes, such as line segment lengths, intersections, angles of intersection, and endpoints are derived by the feature extraction algorithm and employed during model matching. The algebraic operators are global operations which are easily reconfigured to operate on any size or shape region. This provides a natural platform from which to pursue dynamic scene analysis. A method for optimizing the linear feature extractor which capitalizes on the spatially reconfiguration nature of the edge detector/gradient component operator is discussed.

Lerner, Bao-Ting↗
NASA NTRS1992

Closed Ecological Life Support Systems (CELSS) Test Facility

The CELSS Test Facility (CTF) is being developed for installation on Space Station Freedom (SSF) in August 1999. It is designed to conduct experiments that will determine the effects of microgravity on the productivity of higher (crop) plants. The CTF will occupy two standard SSF racks and will accommodate approximately one square meter of growing area and a canopy height of 80 cm. The growth volume will be isolated from the external environment, allowing stringent control of environmental conditions. Temperature, humidity, oxygen, carbon dioxide, and light levels will all be closely controlled to prescribed set points and monitored. This level of environmental control is needed to prevent stress and allow accurate assessment of microgravity effect (10-3 to 10-6 x g). Photosynthetic rates and respiration rates, calculated through continuous recording of gas concentrations, transpiration, and total and edible biomass produced will be measured. Toxic byproducts will be monitored and scrubbed. Transpiration water will be collected within the chamber and recycled into the nutrient solution. A wide variety of crop plants, e.g., wheat, soy beans, lettuce, potatoes, can be accommodated and various nutrient delivery systems and light delivery systems will be available. In the course of its development, the CTF will exploit fully, and contribute importantly, to the state-of-art in closed system technology and plant physiology.

Macelroy, Robert D.↗
NASA NTRS1999

A Whitham-Theory Sonic-Boom Analysis of the TU-144 Aircraft at a Mach Number of 2.2

NASA became interested in the Tu- 144 aircraft when it was offered for use as a "flying testbed" to study operating characteristics of a supersonic-cruise commercial airplane. In addition to the other operational tests being conducted on the Tu- 144 aircraft, it was proposed that two sets of sonic-boom pressure signature measurements be made. One set of tests would consist of ground-level pressure measurements. The second set would be measurements of pressures under the Tu- 144 aircraft in cruise. Pressure gages would be required for this second set of tests: measuring ambient and differential pressures in the flow field of a Tu-144 cruising at supersonic speeds. The range of these gages had to be determined well in advance of the scheduled flights so that they could be installed and calibrated.

Robert J Mack↗
DOE OSTI2025

Glass Property-Composition Models Update for use in Direct Feed High-Level Waste Flowsheet Development

A set of preliminary glass property models and constraints were developed and augmented by models from literature for use in design of direct-feed high-level waste (DFHLW) glasses for flowsheet evaluation, testing, and design of the Tank Waste Treatment and Immobilization Plant (WTP) high-level waste (HLW) Facility. These models and constraints are meant to be used as a place-holder while glass property-composition data gaps are filled and final plant operating models are developed. This report describes the motivation and intended use of the models, the compilation of data, model fitting and selection, methods to apply the models and constraints in glass design and offers example calculations demonstrating their intended use.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

BI-LEVEL OPTIMIZATION FOR ELECTRICITY TRANSACTION IN SMART COMMUNITY WITH MODULAR PUMP HYDRO STORAGE

Grid integration of the increasing distributed energy resources could be challenging in terms of new infrastructure investment, power grid stability, etc. To resolve more renewables locally and reduce the need for extensive electricity transmission, a community energy transaction market is assumed with market operator as the leader whose responsibility is to generate local energy prices and clear the energy transaction payment among the prosumers (followers). The leader and multi-followers have competitive objectives of revenue maximization and operational cost minimization. This non-cooperative leader-follower (Stackelberg) game is formulated using a bi-level optimization framework, where a novel modular pump hydro storage technology (GLIDES system) is set as an upper level market operator, and the lower level prosumers are nearby commercial buildings. The best responses of the lower level model could be derived by necessary optimality conditions, and thus the bi-level model could be transformed into single level optimization model via replacing the lower level model by its Karush-Kuhn-Tucker (KKT) necessary conditions. Several experiments have been designed to compare the local energy transaction behavior and profit distribution with the different demand response levels and different local price structures. The experimental results indicate that the lower level prosumers could benefit the most when local buying and selling prices are equal, while maximum revenue potential for the upper level agent could be reached with non-equal trading prices.

Chen, Yang↗
DOE OSTI2021

Universal Utility Data Exchange (UUDEX) Functional Design Requirements - Rev 1

This document provides a set of high-level functional design requirements for Universal Utility Data Exchange (UUDEX). These requirements include a set of use cases, data exchanges supported by UUDEX, both for grid operations and for cyber security data, functional requirements for data exchange, data models used by UUDEX, data exchange architectures, and security considerations. These functional design requirements are intended to be used in more detailed design documents.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

North Slope of Alaska XSAPR b1 Data Processing Report: May 2025-April 2026

The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility operates an X-band Scanning ARM Precipitation Radar (XSAPR) at the North Slope of Alaska (NSA) atmospheric observatory in Utqiaġvik. This radar provides year-round dual-polarization measurements of snow and ice in an arctic environment. Over the past few years, there has been greater focus on the NSA XSAPR, and recent efforts by ARM staff have resulted in quality-controlled, b-level data (Rocque et al. 2026b). This report outlines the processing of the second set of b-level data released for this radar from May 2025 through April 2026 following similar methods from Rocque et al. (2026b).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

New multi-level codes over GF(q)

Set partitioning to multi-dimensional signal spaces over GF(q), particularly GF sup q-1(q) and GF sup q (q), and show how to construct both multi-level block codes and multi-level trellis codes over GF(q). Two classes of multi-level (n, k, d) block codes over GF(q) with block length n, number of information symbols k, and minimum distance d sub min greater than or = d, are presented. These two classes of codes use Reed-Solomon codes as component codes. They can be easily decoded as block length q-1 Reed-Solomon codes or block length q or q + 1 extended Reed-Solomon codes using multi-stage decoding. Many of these codes have larger distances than comparable q-ary block codes, as component codes. Low rate q-ary convolutional codes, work error correcting convolutional codes, and binary-to-q-ary convolutional codes can also be used to construct multi-level trellis codes over GF(q) or binary-to-q-ary trellis codes, some of which have better performance than the above block codes. All of the new codes have simple decoding algorithms based on hard decision multi-stage decoding.

Wu, Jiantian↗
NASA NTRS1979

Jet noise and performance comparison study of a Mach 2.55 supersonic cruise aircraft

Data provided by the manufacturer relating to noise and performance of a Mach 2.55 supersonic cruise concept employing a post 1985 technology level, variable cycle engine was used to identify differences in noise levels and performance between the manfacturer and NASA associated with methodology and groundrules. In addition, economic and noise information is provided consistent with a previous study based on an advanced technology Mach 2.7 configuration. The results indicate that the difference between the NASA's and manfacturer's performance methodology is small. Resizing the aircraft to NASA groundrules also results in small changes in flyover, sideline and approach noise levels. For the power setting chosen, engine oversizing resulted in no reduction in traded noise. In terms of summated noise level, a 10 EPNdB reduction is realized for an 8 percent increase in total operating costs. This corresponds to an average noise reduction of 3.3 EPNdB at the three observer positions.

Mascitti, V. R.↗
NASA NTRS1992

An advanced environment for spacecraft engineering subsystem mission operations

The Engineering Analysis Subsystem Environment (EASE) is under development at the JPL with a view to prospective small and large space missions. EASE is a modular multimission/multisystem architecture for spacecraft analysis that encompases monitoring and sequence support; its collection of software analysis modules is specific to a given mission, thereby easily accommodating mission scale. An EASE subsystem analysis module can be developed in modular program sets or packages, and a level of automation can then be introduced within such sets to achieve intramodule automation.

Bahrami, K. A.↗
NASA NTRS2016

Integrated Medical Model (IMM) Optimization Version 4.0 Functional Improvements

The IMMs ability to assess mission outcome risk levels relative to available resources provides a unique capability to provide guidance on optimal operational medical kit and vehicle resources. Post-processing optimization allows IMM to optimize essential resources to improve a specific model outcome such as maximization of the Crew Health Index (CHI), or minimization of the probability of evacuation (EVAC) or the loss of crew life (LOCL). Mass and or volume constrain the optimized resource set. The IMMs probabilistic simulation uses input data on one hundred medical conditions to simulate medical events that may occur in spaceflight, the resources required to treat those events, and the resulting impact to the mission based on specific crew and mission characteristics. Because IMM version 4.0 provides for partial treatment for medical events, IMM Optimization 4.0 scores resources at the individual resource unit increment level as opposed to the full condition-specific treatment set level, as done in version 3.0. This allows the inclusion of as many resources as possible in the event that an entire set of resources called out for treatment cannot satisfy the constraints. IMM Optimization version 4.0 adds capabilities that increase efficiency by creating multiple resource sets based on differing constraints and priorities, CHI, EVAC, or LOCL. It also provides sets of resources that improve mission-related IMM v4.0 outputs with improved performance compared to the prior optimization. The new optimization represents much improved fidelity that will improve the utility of the IMM 4.0 for decision support.

risk assessment↗
DOE OSTI2020

Diesel Generator Model Parameterization for Microgrid Simulation Using Hybrid Box-Constrained Levenberg-Marquardt Algorithm

Existing generator parameterization methods, typically developed for large turbine generator units, are difficult to apply to small kW-level diesel generators in microgrid applications. Here, this article presents a model parameterization method that estimates a complete set of kW-level diesel generator parameters simultaneously using only load-step-change tests with limited measurement points. This method provides a more cost-efficient and robust approach to achieve high-fidelity modeling of diesel generators for microgrid dynamic simulation. A two-stage hybrid box-constrained Levenberg-Marquardt (H-BCLM) algorithm is developed to search the optimal parameter set given the parameter bounds. A heuristic algorithm, namely Generalized Opposition-based Learning Genetic Algorithm (GOL-GA), is applied to identify proper initial estimates at the first stage, followed by a modified Levenberg-Marquardt algorithm designed to fine tune the solution based on the first-stage result. The proposed method is validated against dynamic simulation of a diesel generator model and field measurements from a 16kW diesel generator unit.

42 ENGINEERING↗
NASA NTRS1990

Multi-level trellis coded modulation and multi-stage decoding

Several constructions for multi-level trellis codes are presented and many codes with better performance than previously known codes are found. These codes provide a flexible trade-off between coding gain, decoding complexity, and decoding delay. New multi-level trellis coded modulation schemes using generalized set partitioning methods are developed for Quadrature Amplitude Modulation (QAM) and Phase Shift Keying (PSK) signal sets. New rotationally invariant multi-level trellis codes which can be combined with differential encoding to resolve phase ambiguity are presented.

Costello, Daniel J., Jr.↗
DOE OSTI2021

Optimal dimensionality selection for independent component analysis of transcriptomic data

Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals. Applied to high-quality gene expression datasets, independent component analysis effectively reveals both the source signals of the transcriptome as co-regulated gene sets, and the activity levels of the underlying regulators across diverse experimental conditions. Two major variables that affect the final gene sets are the diversity of the expression profiles contained in the underlying data, and the user-defined number of independent components, or dimensionality, to compute. Availability of high-quality transcriptomic datasets has grown exponentially as high-throughput technologies have advanced; however, optimal dimensionality selection remains an open question. We computed independent components across a range of dimensionalities for four gene expression datasets with varying dimensions (both in terms of number of genes and number of samples). We computed the correlation between independent components across different dimensionalities to understand how the overall structure evolves as the number of user-defined components increases. We then measured how well the resulting gene clusters reflected known regulatory mechanisms, and developed a set of metrics to assess the accuracy of the decomposition at a given dimension. We found that over-decomposition results in many independent components dominated by a single gene, whereas under-decomposition results in independent components that poorly capture the known regulatory structure. From these results, we developed a new method, called OptICA, for finding the optimal dimensionality that controls for both over- and under-decomposition. Specifically, OptICA selects the highest dimension that produces a low number of components that are dominated by a single gene. We show that OptICA outperforms two previously proposed methods for selecting the number of independent components across four transcriptomic databases of varying sizes. OptICA avoids both over-decomposition and under-decomposition of transcriptomic datasets resulting in the best representation of the organism’s underlying transcriptional regulatory network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗