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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Improving Resilience of Bus Bunching Holding Strategy through a Rolling Horizon Approach

Providing public transportation with quality service is critical to attracting more passengers to the system. However, high-demand routes are prone to the so-called bus bunching -- a tendency of buses to group as a consequence of variations in travel times and demands. Bus holding is applied to overcome this effect. In this study, we present a novel method for bus holding in which the control law is based only on the buses' position using a computationally efficient rolling horizon approach. The method uses similar inputs as linear control approaches while not increasing significantly the computational time. However, the method overcomes key a weakness of the linear control approach thanks to the explicit constraint handling that always ensures the control action effectiveness. Simulation experiments in a validation case and a model-specific for a bus rapid transit line in Curitiba, Brazil showed a reduced holding time and improved resilience, delivering more than 20% reduction in delay time accounting for the on-board and station delays.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1976

Public policy for solar heating and cooling

Recent analyses indicated that solar heating and cooling systems for residential buildings are nearly economically competitive with conventional fossil fuel or electric systems, the former having higher initial cost but a lower operating cost than the latter. The paper examines obstacles to the widespread acceptance and use of solar space conditioning systems and explores some general policies which could help to overcome them. The discussion covers such institutional barriers limiting the adoption of solar technologies as existing building codes, financing constraints, and organizational structure of the building industry. The potential impact of financial incentives is analyzed. It is noted that a tax incentive of 25% could speed the use of solar energy by 7 to 8 years and produce an 8% reduction in fossil fuel use by 1990. A preliminary incentive package which could be helpful in promoting solar energy both at federal and state levels is proposed, and the necessary incentive level is analysed.

Hirshberg, A. S.↗
NASA NTRS1980

Titan probe technology assessment and technology development plan study

The need for technology advances to accomplish the Titan probe mission was determined by defining mission conditions and requirements and evaluating the technology impact on the baseline probe configuration. Mission characteristics found to be technology drivers include (1) ten years dormant life in space vacuum; (2) unknown surface conditions, various sample materials, and a surface temperature; and (3) mission constraints of the Saturn Orbiter Dual Probe mission regarding weight allocation. The following areas were identified for further development: surface sample acquisition system; battery powered system; nonmetallic materials; magnetic bubble memory devices, and the landing system. Preentry science, reliability, and weight reduction and redundancy must also be considered.

Castro, A. J.↗
NASA NTRS1989

Aeroservoelastic modeling and applications using minimum-state approximations of the unsteady aerodynamics

Various control analysis, design, and simulation techniques for aeroelastic applications require the equations of motion to be cast in a linear time-invariant state-space form. Unsteady aerodynamics forces have to be approximated as rational functions of the Laplace variable in order to put them in this framework. For the minimum-state method, the number of denominator roots in the rational approximation. Results are shown of applying various approximation enhancements (including optimization, frequency dependent weighting of the tabular data, and constraint selection) with the minimum-state formulation to the active flexible wing wind-tunnel model. The results demonstrate that good models can be developed which have an order of magnitude fewer augmenting aerodynamic equations more than traditional approaches. This reduction facilitates the design of lower order control systems, analysis of control system performance, and near real-time simulation of aeroservoelastic phenomena.

Tiffany, Sherwood H.↗
NASA NTRS1988

Statistical corrections to the NMC medium range 700 mb height forecasts

This paper examines four statistical procedures for correcting the NMC medium-range forecast (MRF) errors in the 700-mb heights over the Northern Hemisphere. The tests were designed to include normal operational constraints, such as frequent changes in the forecast model and the lack of long-term forecast histories on which to base estimates of systematic errors and climate drifts. It was found that the two statistical procedures which provided a substantial reduction in mean square error were a procedure based on simple regression correction at each grid point and one based on lagged-average correction with one day lag at each grid point.

Schemm, Jae-Kyung E.↗
NASA NTRS2022

Processing Tomato Production Is Expected to Decrease By 2050 Due to the Projected Increase in Temperature

The global processing tomato production is concentrated in a small number of regions where climate change will have a significant impact on the future supply. Process-based tomato models project that the production in the three main producing countries (the United States, Italy, and China, representing 65% of global production) will decrease 6% by 2050, compared to the baseline period of 1980-2009. The predicted reduction in processing tomato production is due to a simulated increase in air temperature. Under an ensemble of projected climate scenarios, California and Italy might not be able to sustain the current levels of processing tomato production due to water resources constraints. Cooler producing regions, such as China and the northern parts of California, stand to improve their competitive advantage. The projected environmental changes indicate that the main growing regions of processing tomatoes might change in the coming decades.

Tomato production↗
DOE OSTI2023

Online Adaptive Algorithm for Constraint Energy Minimizing Generalized Multiscale Discontinuous Galerkin Method

Here in this research, we propose an online basis enrichment strategy within the framework of a recently developed constraint energy minimizing generalized multiscale discontinuous Galerkin method. Combining the technique of oversampling, one makes use of the information of the current residuals to adaptively construct basis functions in the online stage to reduce the error of multiscale approximation. A complete analysis of the method is presented, which shows the proposed online enrichment leads to a fast convergence from multiscale approximation to the fine-scale solution. The error reduction can be made sufficiently large by suitably selecting oversampling regions and the number of oversampling layers. Further, the convergence rate of the enrichment algorithm depends on a factor of exponential decay regarding the number of oversampling layers and a user-defined parameter. Numerical results are provided to demonstrate the effectiveness and efficiency of the proposed online adaptive algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗
NASA NTRS1989

Performance optimization for rotors in hover and axial flight

Performance optimization for rotors in hover and axial flight is a topic of continuing importance to rotorcraft designers. The aim of this Phase 1 effort has been to demonstrate that a linear optimization algorithm could be coupled to an existing influence coefficient hover performance code. This code, dubbed EHPIC (Evaluation of Hover Performance using Influence Coefficients), uses a quasi-linear wake relaxation to solve for the rotor performance. The coupling was accomplished by expanding of the matrix of linearized influence coefficients in EHPIC to accommodate design variables and deriving new coefficients for linearized equations governing perturbations in power and thrust. These coefficients formed the input to a linear optimization analysis, which used the flow tangency conditions on the blade and in the wake to impose equality constraints on the expanded system of equations; user-specified inequality contraints were also employed to bound the changes in the design. It was found that this locally linearized analysis could be invoked to predict a design change that would produce a reduction in the power required by the rotor at constant thrust. Thus, an efficient search for improved versions of the baseline design can be carried out while retaining the accuracy inherent in a free wake/lifting surface performance analysis.

Quackenbush, T. R.↗
NASA NTRS1997

Optimizing an Actuator Array for the Control of Multi-Frequency Noise in Aircraft Interiors

Techniques developed for selecting an optimized actuator array for interior noise reduction at a single frequency are extended to the multi-frequency case. Transfer functions for 64 actuators were obtained at 5 frequencies from ground testing the rear section of a fully trimmed DC-9 fuselage. A single loudspeaker facing the left side of the aircraft was the primary source. A combinatorial search procedure (tabu search) was employed to find optimum actuator subsets of from 2 to 16 actuators. Noise reduction predictions derived from the transfer functions were used as a basis for evaluating actuator subsets during optimization. Results indicate that it is necessary to constrain actuator forces during optimization. Unconstrained optimizations selected actuators which require unrealistically large forces. Two methods of constraint are evaluated. It is shown that a fast, but approximate, method yields results equivalent to an accurate, but computationally expensive, method.

Palumbo, D. L.↗
NASA NTRS2004

Telescope Scientist on the Advanced X-ray Astrophysics Observatory

In this period, the Chandra X-ray Observatory continued to perform exceptionally well, with many scientific observations and spectacular results. The HRMA performance continues to be essentially identical to that predicted from ground calibration data. The Telescope Scientist Team has improved the mirror model to provide a more accurate description to the Chandra observers, enabling them to reduce the systematic errors and uncertainties in their data reduction. There also has been good progress in the scientific program. Using the Telescope Scientist GTO time, we carried out an extensive Chandra program to observe distant clusters of galaxies. The goals of this program were to use clusters to derive cosmological constraints and to investigate the physics and evolution of clusters. A total of 71 clusters were observed with ACIS-I; the last observations were completed in December 2003.

Smith, Carl M.↗
DOE OSTI2023

Classical and quantum compression for edge computing: the ubiquitous data dimensionality reduction

Edge computing aims to address the challenges associated with communicating and transferring large amounts of data generated remotely to a data center in a timely and efficient manner. A central pillar of edge computing is local (i.e., at- or near-source) data processing capability so that data transfer to a data center for processing can be minimized. Data compression at the edge is therefore a natural component of edge workflows. Here we present a survey of data compression algorithms with a focus on edge computing. Not all compression algorithms can accommodate the data type heterogeneity, tight processing and communication time constraints, or energy efficiency requirement characteristics of edge computing. We discuss specific examples of compression algorithms that are being explored in the context of edge computing. We end our review with a brief survey of emerging quantum compression techniques that are of importance in quantum information processing, including the proposed concept of quantum edge computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Optimizing fluvial flood mitigation strategies: A multi-objective approach for cost-effective and socially-aware infrastructure feasibility analysis

Effective levee planning must balance capital cost, risk reduction, and community priorities. These objectives are rarely optimized together. This study presents a feasibility phase, simulationin-the-loop framework that couples terrain-based flood modeling with a socially aware multiobjective optimizer. Flood risk is measured as Expected Annual Exposed Population (EAEP), obtained by integrating exposure over Annual Exceedance Probability (AEP) nodes, mirroring the Hydrologic Engineering Center's Flood Damage Reduction Analysis (HEC-FDA) expected-annual formulation but with people rather than dollars. Exposure per scenario is computed by overlaying binary inundation masks with a population surface at the tract level. Distributional fairness is encoded through a Group Benefit Share (GBS) constraint that requires high-SVI tracts to receive at least a baseline share of annualized benefits. Capital cost is represented by a height-dependent unit-cost model suitable for screening. This study addresses the two-objective problem, minimize cost and expected annual exposure subject to the GBS constraint, using Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and leveraging Pareto front for feasibility phase decision making. Implemented with terrain-based flood modeling, GeoFlood, for rapid scenario evaluation, the framework is demonstrated in Southeast Texas. The results reveal clear trade-offs among cost, risk, and social benefits and identify non-dominated levee height configurations that satisfy the benefit-share floor. The contributions are a scalable decision support method that operationalizes expected annual population-based risk, embeds enforceable benefit-sharing guarantees, and uses lightweight simulation to explore large design spaces before higher fidelity design stages.

Flood mitigation↗
DOE OSTI2026

Navigating Large Chemical Spaces Using Graph Theory and Integer Programming

Navigating and analyzing large chemical spaces are necessary to accelerate the design and discovery of new molecules and chemical processes. In this work, we introduce a computational framework that integrates graph theory and integer programming to enable the efficient navigation of large chemical spaces. Our framework represents the chemical space as a graph, wherein nodes represent molecules and edges represent the degree of similarity or connectivity based on domain-specific information. Using the graph representation, we identify representative molecules by computing the so-called minimum dominating set (MDS), which in our context is the minimum set of molecules that is connected to all other molecules. We present a suite of solution strategies for the MDS problem including heuristic and rigorous integer programming (IP) approaches. We show that these approaches allow us to capture physicochemical properties and domain-specific logic and constraints, facilitating the identification of molecules with the target properties. We demonstrate the effectiveness of the proposed approach by navigating the chemical space of per- and polyfluoroalkyl substances (PFAS); this comprises approximately 15,000 molecular structures. We compare our framework against traditional dimensionality reduction and clustering methods such as t-SNE and K-means clustering.

Chemical structure↗
DOE OSTI2024

Optimization of foreground moment deprojection for semi-blind CMB polarization reconstruction

Abstract Upcoming Cosmic Microwave Background (CMB) experiments, aimed at measuring primordial CMB polarization B-modes, require exquisite control of instrumental systematics and Galactic foreground contamination. Blind minimum-variance techniques, like the Needlet Internal Linear Combination (NILC), have proven effective in reconstructing the CMB polarization signal and mitigating foregrounds and systematics across diverse sky models without suffering from foreground mismodelling errors. Still, residual foreground contamination from NILC may bias the recovered CMB polarization at large angular scales when confronted with the most complex foreground scenarios.By adding constraints to NILC to deproject statistical moments of the Galactic emission, the Constrained Moment ILC (cMILC) method has been demonstrated to further enhance foreground subtraction, albeit with an associated increase in overall noise variance. Faced with this trade-off between foreground bias reduction and overall variance minimization, there is still no recipe on which moments to deproject and which are better suited for blind variance minimization. To address this, we introduce the optimized cMILC (ocMILC) pipeline, which performs full automated optimization of the required number and set of foreground moments to deproject, pivot parameter values, and deprojection coefficients across the sky and angular scales, depending on the actual sky complexity, available frequency coverage, and experiment sensitivity. The optimal number of moments for deprojection, before paying significant noise penalty, is determined through a data diagnosis inspired by the Generalized NILC (GNILC) method.Validated on B-mode simulations of thePICOspace mission concept with four challenging foreground models, ocMILC exhibits lower Galactic foreground contamination compared to NILC and cMILC at all angular scales, with limited noise penalty. This multi-layer optimization enables the ocMILC pipeline to achieve unbiased posteriors of the tensor-to-scalar ratio, regardless of foreground complexity.

Astronomy & Astrophysics↗
DOE OSTI2023

Multi-Sourced Collaboration for the Production and Refining of Rare Elements and Critical Metals (Final Technical Report)

The project objective was to develop a feasible and cost-effective method for recovering rare earth elements (REEs) and critical materials (CMs) from coal and coal byproducts, resulting in high-purity individually separated REEs and CMs. The targeted REEs included Y, Pr, Nd, Gd, Dy, and Sm, with a purity of over 99.5%, while the CMs included Co, Mn, Ga, Sr, Li, Ni, Zn, and Ge, with a purity of over 90%. The project aimed to design a prototype facility capable of producing 1-3 tonnes/day of high-purity REO mixes. The work was divided into four designated circuits: 1) REE extraction and concentration, 2) REE separation and purification, 3) RE metal production, and 4) CM production. To achieve these goals, the project involved 11 tasks, including technology reviews, research, process flow diagram development, mass balance estimation, and preliminary technical-economic analysis. The project team included researchers from the University of Kentucky, University of Alabama and Virginia Tech as well as process specialists from Argonne National Laboratory. MP Materials provided technical support regarding rare earth markets and processing while Alliance Coal performed resource assessment. The project included a market analysis for Nd/Pr, Tb, Dy, Gd, Y, Co, Mn, Li, Sr, Ga, Ni, Zn, and Ge. These analyses provided insights into the supply and demand trends as well as historic and future projections of market price relative to purity requirements for these elements. Two coal resources were selected for the project: the West Kentucky No. 13 (Baker) Seam and an undisclosed lignite resource in the Illinois coal basin. The estimated quantities of REEs in these resources were calculated based on production samples and drilling data. It was estimated that there is adequate supply for an operation producing one metric ton daily of higher purity mixed rare earth oxides (MREO) for approximately 20 years at a site located in western Kentucky. In Circuit 1, project data was obtained from a pilot heap leach and REE concentration facility. It was concluded that the existing circuit, which generated a MREO concentrate, two types of CM mixed products, and Li- and Sr-containing waters, would be suitable feed for circuits 2-4. Data from the first-of-its-kind coal coarse refuse heap leach pilot pad played a crucial role in estimating reliable elemental concentrations of the pregnant leaching solution (PLS). The average total REE concentration in the PLS was found to be 28.6 ppm. In Circuit 2, several concepts were explored including a novel process referred to as solvent-assisted chromatography (SAC). This concept involved a novel columnar reactor that incorporated multiple mixer/settlers, thereby enabling the operation of counter-flowing aqueous and organic phases. Unfortunately, due to project time constraints, a complete fundamental modeling analysis could not be completed to fully evaluate the technology. Molten salt electrowinning was considered as an alternative for circuit 3 following circuit 2 purification circuit utilizing the novel SAC process. A mass and energy balance of Nd reduction to metal in a fluoride containing molten salt electrolyte was conducted. Comparisons were made with the current state of Asian molten salt electrorefining, and potential improvements in siphoning rare earth metals (REM) from the reactor were presented. A cost estimate was performed for the production of 1 tonne per day, which yielded a total of $2.29 million for the nine electrowinning (EW) cells required. The selected option for circuits 2 and 3 was a plasma distillation process, which initially separates rare earth elements (REEs) from other elements. This is followed by selective electrowinning in various ionic liquids. The selection was made on the basis of thermodynamic modeling and experimental data previously published by a project partner. The combination offers an innovative approach to integrated refining and RE metal production. For Circuit 4, an extensive literature review was conducted for the processing of the CMs. The ultimate decision was to utilize a combined plasma and ionic liquid process as well to produce individual high-purity concentrates of Zn, Ni, Co, Mn, and Mg. A separate flowsheet for Li and Sr was recommended, which would yield carbonates of these elements. Due to the lack of suitable experimental data at this time, a process recommendation could not be provided but several methods have been proposed for consideration. Lastly, a techno-economic analysis (TEA) was conducted to assess the effectiveness of the proposed process for further investigation. The TEA results revealed a capital expense (CapEx) of $737 million and an annual operational expense (OpEx) of $220 million. Due to the selected elements, the hypothetical heap leach pad can produce 1 metric tonne per day of REO equivalent, but a conscious decision was made to only treat targeted REEs, resulting in the production of 0.4 metric tonne of REM. An estimated annual revenue of $90.87 million was projected based on standard market pricing information provided by the funding agency. During the TEA, ten different modules were evaluated for costing purposes. The precipitation circuit was identified as the largest single operational expense, followed by the Mg/Mn process due to the amount of treated metal. In terms of capital expenditures, the heap leach process incurred the highest cost, followed by the Mg/Mn process. The scalability of the plasma process is a crucial consideration since the reactors cannot be scaled beyond the largest demonstrated size due to their reliance on surface area of the slag and vapor phase. The purity estimate for the REEs are generally 98%±2% to produce a metal. The purity level being lower than the project objective was due to the lack of specific experimental data needed to tighten the tolerance of the estimates. Based on literature and previous experience, the CMs are estimated as follows; Ga (95%+, metal), Sr (95%+, carbonate), Li (95%+, carbonate), Ni (98%±2%, metal), Zn (95%+, metal sponge), Ge (95%+, metal), Co (98%±2%, metal), and Mn (98%±2%, metal).

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

A Unified Beam-Dynamics and Hardware Design Framework for Hybrid Nonlinear-Kicker Injection in NSLS-II

Nonlinear kickers (NLKs) enable off-axis injection in ultralow-emittance storage rings by providing a strong kick to the injected beam while remaining nearly transparent to the stored beam. In hybrid schemes, a conventional four-kicker bump defines the injected trajectory, and the NLK reduces the first-turn action under constrained beam offset and optics conditions. Effective operation additionally requires stable and reproducible first-turn injection trajectories. We develop a compact action–angle framework that expresses NLK dynamics in terms of Courant–Snyder invariants and yields an analytical bound on achievable action reduction. This formulation provides direct design rules for NLK placement, phase advance, injected-beam offset, and kicker field profile. Within this framework, we identify the 8-wire NLK as a practical baseline and extend its design by relaxing the square-geometry constraint, enabling inward shifting of the off-axis field peak while preserving on-axis field and gradient cancellation. Application to the NSLS-II lattice shows how aperture, pulsed-power, and mechanical constraints combine to determine a coupled design solution. Multi-turn tracking confirms that candidate NLK locations maintain sufficient stay-clear (aperture-clearance) margin, while the optimized wire geometry reduces the required current and Lorentz force load. The results establish a unified approach for NLK-assisted injection design and provide a practical pathway for upgrades in diffraction-limited storage rings.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Integrated multidisciplinary rotorcraft optimization research at the NASA Langley Research Center

NASA-Langley and U.S. Army researchers have developed optimization procedures for improving helicopter rotor blade design processes through more extensive integration of the requisite disciplines. These disciplines encompass rotor aerodynamics, rotor dynamics, rotor structures, airframe dynamics, and acoustics. In the first phase of this integrated optimization approach, acoustics and airframe aerodynamics are decoupled and accounted for as effective constraints on the design for the first three disciplines. In phase two, acoustics is integrated with the first three disciplines; in phase three, airframe dynamics are integrated with the other four disciplines. Representative results are presented from recent work on blade shear force reduction and aerodynamic/dynamic optimization.

Adelman, Howard M.↗