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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Technology Assessment for Large Vertical-Lift Transport Tiltrotors

The technical community has identified rotor efficiency as a critical enabling technology for large vertical-lift transport (LVLT) rotorcraft. The size and performance of LVLT aircraft will be far beyond current aircraft capabilities, enabling a transformational change in cargo transport effectiveness. Two candidate approaches for achieving high efficiency were considered for LVLT applications: a variable-diameter tiltrotor (VDTR) and a variable-speed tiltrotor (VSTR); the former utilizes variable-rotor geometry and the latter utilizes variable-rotor speed. Conceptual aircraft designs were synthesized for the VDTR and VSTR and compared to a conventional tiltrotor (CTR). The aircraft were optimized to a common objective function and bounded by a set of physical- and requirements-driven constraints. The resulting aircraft were compared for weight, size, performance, handling qualities, and other attributes. These comparisons established a measure of the relative merits of the variable-diameter and -speed rotor systems as enabling technologies for LVLT capability.

Germanowski, Peter J.↗
NASA NTRS2018

Polarization Ray Tracing and Polarization Aberration Compensation in Reflective Astronomical Telescopes

Assessing and optimizing polarization performance in the context of ray-based optical design can be challenging. We describe an approach to this problem that decouples polarization effects from optical system geometry for reflective systems. Each surface's polarization properties are parameterized in terms of their impact on retardance and diattenuation in the small angle-of-incidence limit, separating polarization assessment from the task of coating design. A low-resolution ray trace of the system is adequate to determine ray geometry at each interface, which can then be interpolated to rapidly evaluate net Jones Matrix pupil functions. Coating behavior can be easily varied using the ellipsometric parameters to investigate impacts and compensation. Desired values of these parameters can then be specified as constraints in coating design. Investigation with candidate telescope optical designs for LUVOIR show baseline root-mean-square wavefront errors in the nm range for the on-diagonal Jones matrix component, and throughputs of tens of parts per million. Promising possibilities for compensation using a purpose-designed coating on the secondary mirror are discussed, which reduce the on-diagonal wavefront error by a factor 20, with accompanying but more modest reductions in coupling into off-diagonal terms.

Sabatke, Derek↗
DOE OSTI2026

Custom surface reflectance, shade mask, and equivalent water thickness maps for the Colorado Headwaters Ecological Spectroscopy Study (2025)

This dataset contains land surface reflectance estimates and additional derived products generated from NEON Imaging Spectrometer (NIS) data collected in the Upper Gunnison river basin during June and July of 2025. Data was collected over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). These products were derived from radiance and LiDAR data collected by the NEON Airborne Observation Platform (AOP) campaign funded by the Colorado Headwaters Ecological Spectroscopy Study (CHESS) (doi:10.15485/3017965). Products include per-pixel surface reflectance (rfl) and reflectance uncertainty (rfl_unc), observational data (obs), canopy equivalent water thickness (ewt), and shade masks. Atmospheric correction was performed per flightline using the ISOFIT (Imaging Spectrometer Optimal FITting) optimal estimation framework to estimate surface reflectance and the associated per-band reflectance uncertainty. Reflectance retrievals achieved a mean absolute error of 1.5% across diverse validation surfaces (see validation report.pdf). Equivalent water thickness was calculated from surface reflectance using the Beer–Lambert absorption of liquid water. Shade masks were generated based on the geometry between the sun angle, ground surface, and sensor at the time of flight. Data products are provided per-flightline and as mosaics for each domain. Flightline data products are provided as ENVI-formatted binary files (rfl, rfl_unc, ewt) and GeoTIFFs (shade). Reflectance and uncertainty mosaics are provided as tiled NetCDFs, while all other mosaicked products are provided as cloud-optimized GeoTIFFs. These formats are supported by common geospatial software (e.g., QGIS, ArcGIS, ENVI) and programmatic libraries in Python (e.g., rasterio, xarray, spectral, netCDF4) and R (e.g., terra, ncdf4). Processing workflows were designed to be equivalent to those used to generate the 2018 CHESS campaign airborne imaging spectroscopy data products (doi:10.15485/3013527). All outputs were co-registered to a common spatial grid to support time series analyses. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: Data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). Computational research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004) and was funded by EMIT Extended Mission Phase E Science.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2023

Surface Merging Technique to Design GA-Optimized Heat Sinks

High-power density inverters require efficient and small heat dissipation systems. For liquid cooling systems, an effective heat sink design is important to enable higher heat transfer and keep the pressure drop within reasonable limits. A heat sink geometry generated from an extruded, 1D fast Fourier transform can achieve more even temperature distribution and improved heat transfer than a conventional heat sink. Building on this concept, this paper proposes a new heat sink geometry creation algorithm. Instead of one plane profile being extruded, multiple plane profiles, each created from the fast Fourier transform method, are subsequently merged by smooth surfaces along the flow direction of the heat sink. Thus, a 3D heat sink geometry is created that enables 3D coolant flow and efficient heat transfer. The volume of this design was reduced by 50% compared with pin fin heat sinks. Compared with extruded 1D fast Fourier transform heat sinks, the proposed design showed an approximately 5% device temperature reduction and a 20% pressure drop reduction.

Barua, Himel↗
NASA NTRSDate not supplied

Aviary: An Open-Source Multidisciplinary Design, Analysis, and Optimization Tool for Modeling Aircraft with Analytic Gradients

In recent years demands on aircraft design methods have begun to require higher degrees of coupling between disciplines and optimization in order to satisfy competing objectives involving large numbers of design parameters that define unconventional configurations. These expanding requirements have amplified a need for new and improved aircraft design, analysis, and optimization codes that are capable of performing coupled design and exploiting analytic gradients to perform gradient-based optimization where possible. To address this need, a new multidisciplinary design optimization and analysis tool called Aviary is presented. This tool, built on OpenMDAO, allows for tightly coupled, simultaneous aircraft and subsystem design using analytic gradients. Aviary includes methods from two NASA developed legacy aircraft analysis tools and provides native analytically differentiated calculations for five different disciplines (weights and sizing, aerodynamics, geometry, propulsion, and mission analysis), while also allowing external discipline analysis tools to be coupled, regardless of whether those tools can provide analytic gradients. Verification and preliminary examples and modeling efforts show Aviary’s ability to effectively model novel concepts and explore large and non-intuitive design spaces. Additionally, a multi-level user interface in Aviary creates an easy entry point for users with any level of multidisciplinary design, analysis, and optimization experience.

optimization↗
DOE OSTI2021

Current Status of Radiopharmaceutical Therapy

In radiopharmaceutical therapy (RPT), a radionuclide is systemically or locally delivered with the goal of targeting and delivering radiation to cancer cells while minimizing radiation exposure to untargeted cells. Examples of current RPTs include thyroid ablation with the administration of {sup 131}I, treatment of liver cancer with {sup 90}Y microspheres, the treatment of bony metastases with {sup 223}Ra, and the treatment of neuroendocrine tumors with {sup 177}Lu-DOTATATE. New RPTs are being developed where radionuclides are incorporated into systemic targeted therapies. To assure that RPT is appropriately implemented, advances in targeting need to be matched with advances in quantitative imaging and dosimetry methods. Currently, radiopharmaceutical therapy is administered by intravenous or locoregional injection, and the treatment planning has typically been implemented like chemotherapy, where the activity administered is either fixed or based on a patient’s body weight or body surface area. RPT pharmacokinetics are measurable by quantitative imaging and are known to vary across patients, both in tumors and normal tissues. Therefore, fixed or weight-based activity prescriptions are not currently optimized to deliver a cytotoxic dose to targets while remaining within the tolerance dose of organs at risk. Methods that provide dose estimates to individual patients rather than to reference geometries are needed to assess and adjust the injected RPT dose. Accurate doses to targets and organs at risk will benefit the individual patients and decrease uncertainties in clinical trials. Imaging can be used to measure activity distribution in vivo, and this information can be used to determine patient-specific treatment plans where the dose to the targets and organs at risk can be calculated. The development and adoption of imaging-based dosimetry methods is particularly beneficial in early clinical trials. In this work we discuss dosimetric accuracy needs in modern radiation oncology, uncertainties in the dosimetry in RPT, and best approaches for imaging and dosimetry of internal radionuclide therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Deep learning closure models for large-eddy simulation of flows around bluff bodies

Near-wall flow simulation remains a central challenge in aerodynamics modelling: Reynolds-averaged Navier–Stokes predictions of separated flows are often inaccurate, and large-eddy simulation (LES) can require prohibitively small near-wall mesh sizes. A deep learning (DL) closure model for LES is developed by introducing untrained neural networks into the governing equations and training in situ for incompressible flows around rectangular prisms at moderate Reynolds numbers. The DL-LES models are trained using adjoint partial differential equation (PDE) optimization methods to match, as closely as possible, direct numerical simulation (DNS) data. They are then evaluated out-of-sample – for aspect ratios, Reynolds numbers and bluff-body geometries not included in the training data – and compared with standard LES models. The DL-LES models outperform these models and are able to achieve accurate LES predictions on a relatively coarse mesh (downsampled from the DNS mesh by factors of four or eight in each Cartesian direction). We study the accuracy of the DL-LES model for predicting the drag coefficient, near-wall and far-field mean flow, and resolved Reynolds stress. A crucial challenge is that the LES quantities of interest are the steady-state flow statistics; for example, a time-averaged velocity component $\langle {u}_i\rangle (x) = \lim _{t \rightarrow \infty } ({1}/{t}) \int _0^t u_i(s,x)\, {\rm d}s$ . Calculating the steady-state flow statistics therefore requires simulating the DL-LES equations over a large number of flow times through the domain. It is a non-trivial question whether an unsteady PDE model with a functional form defined by a deep neural network can remain stable and accurate on $t \in [0, \infty )$ , especially when trained over comparatively short time intervals. Our results demonstrate that the DL-LES models are accurate and stable over long time horizons, which enables the estimation of the steady-state mean velocity, fluctuations and drag coefficient of turbulent flows around bluff bodies relevant to aerodynamics applications.

Mechanics↗
DOE OSTI2025

TorbeamNN: machine learning-based steering of ECH mirrors on KSTAR

We have developed TorbeamNN: a machine learning surrogate model for the TORBEAM ray tracing code to predict electron cyclotron heating (ECH) and current drive locations in tokamak plasmas. TorbeamNN provides more than a 100 times speed-up compared to the highly optimized and simplified real-time implementation of TORBEAM without any reduction in accuracy compared to the offline, full fidelity TORBEAM code. The model was trained using KSTAR ECH mirror geometries and works for both O-mode and X-mode absorption. The TorbeamNN predictions have been validated both offline and real-time in experiment. TorbeamNN has been utilized to track an ECH absorption vertical position target in dynamic KSTAR plasmas as well as under varying toroidal mirror angles and with a minimal average tracking error of 0.5 cm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

NSTX-U research advancing the physics of spherical tokamaks

Abstract The objectives of NSTX-U research are to reinforce the advantages of STs while addressing the challenges. To extend confinement physics of low- A , high beta plasmas to lower collisionality levels, understanding of the transport mechanisms that set confinement performance and pedestal profiles is being advanced through gyrokinetic simulations, reduced model development, and comparison to NSTX experiment, as well as improved simulation of RF heating. To develop stable non-inductive scenarios needed for steady-state operation, various performance-limiting modes of instability were studied, including MHD, tearing modes, and energetic particle instabilities. Predictive tools were developed, covering disruptions, runaway electrons, equilibrium reconstruction, and control tools. To develop power and particle handling techniques to optimize plasma exhaust in high performance scenarios, innovative lithium-based solutions are being developed to handle the very high heat flux levels that the increased heating power and compact geometry of NSTX-U will produce, and will be seen in future STs. Predictive capabilities accounting for plasma phenomena, like edge harmonic oscillations, ELMs, and blobs, are being tested and improved. In these ways, NSTX-U researchers are advancing the physics understanding of ST plasmas to maximize the benefit that will be gained from further NSTX-U experiments and to increase confidence in projections to future devices.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

A Cryogenic readout integrated circuit with analog pile-up and in-Pixel ADC for high frame rate Skipper CCD-in-CMOS Sensors

The Skipper CCD-in-CMOS Parallel Read-Out Circuit V2 (SPROCKET2) is designed to enable high frame rate readout of Skipper CCD-in-CMOS image sensors. The SPROCKET2 pixel is fabricated in a 65 nm CMOS process and occupies a 60$\mu$m $\times$ 60$\mu$m footprint. SPROCKET2 is intended to be heterogeneously integrated with a pixelated Skipper CCD-in-CMOS sensor, such that one readout pixel is connected to a multiplexed array of 16 active image sensor pixels, to match their spatial geometry. Our design benefits from the Skipper CCD-in-CMOS sensor's non-destructive readout capability to achieve exceptionally low noise through multi-sampling and averaging while optimizing for total power consumption. The pixel readout utilizes correlated double sampling to minimize 1/f noise and includes "pile-up" of ten successive samples in the analog domain before digitizing at a rate of 66.7 ksps. Measurement results of in-pixel serial SAR ADC show DNL and INL of ~0. 44 LSB and 0.58 LBS respectively. A large area array of 20,000 SPROCKET2 ADC pixels (multiplexed 1:16 to 320,000 sensor pixels) is currently under test. By reading out data over a 10 Gbps optical link, this pixel design enables a frame rate of $\sim$ 4 kfps for large sensing areas with minimal sensing deadtime. In the highest gain mode, the pixelated ADC has an input-referred resolution of 10$\mu$V with a simulated power consumption of 50$\mu$W. The pixel operates with constant current draw to minimize power-rail crosstalk.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Memory-Aware External Facelist Calculation: A Data-Parallel Atomic Hash Counting Approach

Unstructured volumetric meshes serve as fundamental data representations in various scientific simulations and analyses. They play a crucial role in representing complex computational domains and are essential for important numerical techniques, such as finite element analysis. Whenever such a mesh is read from a file, streamed in-situ, or generated by algorithms, scientific visualization libraries rely on calculating the external surface of a geometry, named “external facelist”, to produce a polygonal mesh for rendering. Consequently, external facelist calculation has become one of the most widely used algorithms in the scientific visualization domain, necessitating optimal performance. In this paper, we explore relevant work on external facelist calculation algorithms in two common visualization libraries, VTK and Viskores, assess their performance and memory constraints, and introduce a novel memory-aware external facelist calculation algorithm employing an atomic hash counting approach. This algorithm fully leverages Viskores' data-parallel primitive operations, facilitating its execution across diverse many-core architectures. Our algorithm features the lowest memory footprint on the GPU and the second-lowest on the CPU among all evaluated methods, and it also delivers the fastest performance on both CPU and GPU. It has been made available under an open-source license in the VTK and Viskores visualization systems.

Tsalikis, Spiros [Kitware] (ORCID:0000000151137195↗
DOE OSTI2024

LAMP RFQ vane tip macro-based 3D modeling

This report covers the workflow and the demonstration of modeling the radiofrequency quadrupole (RFQ) vane tip geometry in 3D, for the Front End Upgrade of the LANSCE Modernization Project (LAMP). The goal is to develop an automated procedure to generate the 3D model of the LAMP RFQ vane tip geometry, so as to eliminate the need to manually enter the design parameters for each RFQ cell, when building the 3D model. With the developed procedure, the LAMP RFQ design optimization work can be significantly more efficient.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Ensemble Manufacturing Techniques for Steam Turbine Components Across Length Scales

Faster design to manufacturing requirements were sought for steam turbine components to meet the changing demands of today’s power grid of improved efficiency through operating temperature increases and enhanced operational flexibility from baseload to cyclic operations. Advances in multiple advanced manufacturing (AM) process enabled redesign of turbine components for extreme environments with the potential to reduce cost. AM is of particular interest to improve component functionality, higher temperature capability, and superior durability in large scale steam turbine applications. AM methods have an immense potential to open-up the design space by working directly with the 3D model to produce near-net shapes, enable fast design-manufacturing iterations, thereby significantly reducing product cost and lead-time up to 25 % from current baseline. However, these benefits cannot be fully realized due to the potential for unknown AM processing defects and their resultant effect upon component performance in service. Siemens is partnering with Oak Ridge National Laboratory (ORNL), Electric Power Research Institute (EPRI), and Connecticut Center for Advanced Technology (CCAT) to advance the knowledge of complex process-material interactions for desired microstructures and properties that are closely interlinked to component geometries across different length scales. The proposed program utilized an ensemble of multidisciplinary technologies to accelerate the development of materials, high-throughput experiments for their qualification, and design flexibility/topology optimization for repair/redesign of components to address critical failure mechanisms for improved performance and increased reliability of existing power plant components. The proposed activities, if successfully demonstrated for identified components, will enable paradigm shift in customized manufacturing and accelerated qualification/certification towards increased steam turbine component durability, increased turbine efficiency, and reduced CO 2 emissions in load-following environments compared to today’s technology. Technology maturation is built into the project as successful research will include customized process-component down-selection enabling AM methodologies to be incorporated directly into the existing supply chain. The specific activities of the proposed effort are: 1. Topology optimization of down-selected steam turbine parts that are amenable to additive and hybrid manufacturing for cost/performance improvement. 2. Process-structure-property relationships for five AM processes for steam turbine materials of interest to compare with conventional materials. 3. Perform part/assembly build process using advanced additive/hybrid machine tools followed by quality inspection of the built components for insight into qualification for production scale-up. Steam turbine rig testing of printed components under targeted, well monitored and characterized environmental conditions of for performance comparison of baseline and redesigned components.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Flexible Tool for Beam Induced Background Simulations at a Muon Collider

A Muon Collider represents a very interesting possibility for a future machine to explore the energy frontier in particle physics.However, to reach the needed luminosity, beam intensities of the order of $10^{9-11}$ muons per bunch are needed. In this context, the Beam Induced Background must be taken into account for its effects on the magnets and on the detector. Several optimizations can be conceived with the aim to mitigate them. In this view, it is of crucial importance to develop a flexible tool that allows to easily reconstruct the machine geometry in a Monte Carlo code, allowing to simulate in detail the interaction of muon decay products in the machine, while being able to change the machine optics itself to find the best configuration.In this contribution, a possible approach to such a purpose is presented, based on FLUKA for the Monte Carlo simulation and on LineBuilder for the geometry reconstruction.First results for the 1.5TeV machine optics developed by the MAP collaboration are discussed in this paper.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1979

Orbit Transfer Vehicle Engine Study. Phase A, extension 1: Advanced expander cycle engine optimization

The performance optimization of expander cycle engines at vacuum thrust levels of 10K, 15K, and 20K lb is discussed. The optimization is conducted for a maximum engine length with an extendible nozzle in the retracted position of 60 inches and an engine mixture ratio of 6.0:1. The thrust chamber geometry and cycle analyses are documented. In addition, the sensitivity of a recommended baseline expander cycle to component performance variations is determined and chilldown/start propellant consumptions are estimated.

Mellish, J. A.↗
NASA NTRS1992

Consecutive plate acoustic suppressor apparatus and methods

An apparatus and method for suppressing acoustic noise utilizes consecutive plates, closely spaced to each other so as to exploit dissipation associated with sound propagation in narrow channels to optimize the acoustic resistance at a liner surface. The closely spaced plates can be utilized as high temperature structural materials for jet engines by constructing the plates from composite materials. Geometries of the plates, such as plate depth, shape, thickness, inter-plate spacing, arrangement, etc., can be selected to achieve bulk material-like behavior.

Doychak, Joseph↗
NASA NTRS1995

Rapid deceleration mode evaluation

Aircraft with flight capability above 1.4 normally have an RPM lockup or similar feature to prevent inlet buzz that would occur at low engine airflows. This RPM lockup has the effect of holding the engine thrust level at the intermediate power (maximum non-afterburning). For aircraft such as military fighters or supersonic transports, the need exists to be able to rapidly slow from supersonic to subsonic speeds. For example, a supersonic transport that experiences a cabin decompression needs to be able to slow/descend rapidly, and this requirement may size the cabin environmental control system. For a fighter, there may be a desire to slow/descend rapidly, and while doing so to minimize fuel usage and engine exhaust temperature. Both of these needs can be aided by achieving the minimum possible overall net propulsive force. As the intermediate power thrust levels of engines increase, it becomes even more difficult to slow rapidly from supersonic speeds. Therefore, a mode of the performance seeking control (PSC) system to minimize overall propulsion system thrust has been developed and tested. The rapid deceleration mode reduces the engine airflow consistent with avoiding inlet buzz. The engine controls are trimmed to minimize the thrust produced by this reduced airflow, and moves the inlet geometry to degrade the inlet performance. As in the case of the other PSC modes, the best overall performance (in this case the least net propulsive force) requires an integrated optimization of inlet, engine, and nozzle variables. This paper presents the predicted and measured results for the supersonic minimum thrust mode, including the overall effects on aircraft deceleration.

Conners, Timothy R.↗