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At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

NASA NTRS1995

Scramjet Performance Assessment Using Water Absorption Diagnostics (U)

Simultaneous multiple path measurements of temperature and H2O concentration will be presented for the AIMHYE test entries in the NASA Ames 16-Inch Shock Tunnel. Monitoring the progress of high temperature chemical reactions that define scramjet combustor efficiencies is a task uniquely suited to nonintrusive optical diagnostics. One application strategy to overcome the many challenges and limitations of nonintrusive measurements is to use laser absorption spectroscopy coupled with optical fibers. Absorption spectroscopic techniques with rapidly tunable lasers are capable of making simultaneous measurements of mole fraction, temperature, pressure, and velocity. The scramjet water absorption diagnostic was used to measure combustor efficiency and was compared to thrust measurements using a nozzle force balance and integrated nozzle pressures to develop a direct technique for evaluating integrated scramjet performance. Tests were initially performed with a diode laser tuning over a water absorption feature at 1391.7 nm. A second diode laser later became available at a wavelength near 1343.3 nm covering an additional water absorption feature and was incorporated in the system for a two-wavelength technique. Both temperature and mole fraction can be inferred from the lineshape analysis using this approach. Additional high temperature spectroscopy research was conducted to reduce uncertainties in the scramjet application. The lasers are optical fiber coupled to ports at the combustor exit and in the nozzle region. The output from the two diode lasers were combined in a single fiber, and the resultant two-wavelength beam was subsequently split into four legs. Each leg was directed through 60 meters of optical fiber to four combustor exit locations for measurement of beam intensity after absorption by the water within the flow. Absorption results will be compared to 1D combustor analysis using RJPA and nozzle CFD computations as well as to data from a nozzle metric balance measuring thrust and integrated pressure measurements along the length of the nozzle. Assessment of its value as a combustor performance evaluation tool will be conducted.

Cavolowsky, John A.↗

DOE OSTI2025

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Exploring Object Detection and Image Classification Tasks for Niche Use Case in Naturalistic Driving Studies

Naturalistic driving studies consist of drivers using their personal vehicles and provide valuable real-world data, but privacy issues must be handled very carefully. Drivers sign a consent form when they elect to participate, but passengers do not for a variety of practical reasons. However, their privacy must still be protected. One large study includes a blurred image of the entire cabin which allows reviewers to find passengers in the vehicle; this protects the privacy but still allows a means of answering questions regarding the impact of passengers on driver behavior. A method for automatically counting the passengers would have scientific value for transportation researchers. We investigated different image analysis methods for automatically locating and counting the non-drivers including simple face detection and fine-tuned methods for image classification and a published object detection method. We also compared the image classification using convolutional neural network and vision transformer backbones. Our studies show the image classification method appears to work the best in terms of absolute performance, although we note the closed nature of our dataset and nature of the imagery makes the application somewhat niche and object detection methods also have advantages. We perform some analysis to support our conclusion.

Peruski, Ryan↗

DOE OSTI2022

n-Type doping of a solution processed p-type semiconductor using isoelectronic surface dopants for homojunction fabrication

The p-n junction is one of the fundamental requirements for a practical semiconductor-based electronic device. Designing a heterojunction comprising of dissimilar p-type and n-type semiconductors calls for careful energy level considerations, both when selecting the semiconductor materials as well as the metal contacts. A homojunction based on a single semiconductor simplifies this task, as energy levels of the p-type and n-type materials are already fairly similar, allowing for easier selection of contacts. Traditionally, homojunctions rely on doping of a bulk semiconductor to achieve p- and n-type transport through controlled addition of aliovalent dopants via energy-intensive processes such as ion implantation or thermal annealing. Exact control of doping in nanocrystalline semiconductors is significantly more challenging, due to self-purification effects. However, owing to their large surface areas, surface moieties can be utilized to both dope the nanostructures as well as tune their energy levels. Here, we present a facile technique based on an isoelectronic surface dopant in order to achieve p- and n-type materials based on the same semiconductor. We show that thin p-type colloidal Bi 2 Te 3 nanowires can be switched to n-type through surface functionalization, thus increasing the availability of new nanocrystalline solution-processable p-n homojunctions.

42 ENGINEERING↗

NASA NTRS2008

Developing Humanoid Robots for Real-World Environments

Humanoids are steadily improving in appearance and functionality demonstrated in controlled environments. To address the challenges of operation in the real-world, researchers have proposed the use of brain-inspired architectures for robot control, and the use of robot learning techniques that enable the robot to acquire and tune skills and behaviours. In the first part of the paper we introduce new concepts and results in these two areas. First, we present a cerebellum-inspired model that demonstrated efficiency in the sensory-motor control of anthropomorphic arms, and in gait control of dynamic walkers. Then, we present a set of new ideas related to robot learning, emphasizing the importance of developing teaching techniques that support learning. In the second part of the paper we propose the use in robotics of the iterative and incremental development methodologies, in the context of practical task-oriented applications. These methodologies promise to rapidly reach system-level integration, and to early identify system-level weaknesses to focus on. We apply this methodology in a task targeting the automated assembly of a modular structure using HOAP-2. We confirm this approach led to rapid development of a end-to-end capability, and offered guidance on which technologies to focus on for gradual improvement of a complete functional system. It is believed that providing Grand Challenge type milestones in practical task-oriented applications accelerates development. As a meaningful target in short-mid term we propose the 'IKEA Challenge', aimed at the demonstration of autonomous assembly of various pieces of furniture, from the box, following included written/drawn instructions.

Stoica, Adrian↗

DOE OSTI2025

Automatic building energy model development and debugging using large language models agentic workflow

Building energy modeling (BEM) is a complex process that demands significant time and expertise, limiting its broader application in building design and operations. While Large Language Models (LLMs) agentic workflow have facilitated complex engineering processes, their application in BEM has not been specifically explored. This paper investigates the feasibility of automating BEM using LLM agentic workflow. Here, we developed a generic LLM-planning-based workflow that takes a building description as input and generates an error-free EnergyPlus building energy model. Our robust workflow includes four core agents: 1) Building Description Pre-Processing, 2) IDF Object Information Extraction, 3) Single IDF Object Generator Suite, and 4) IDF Debugging Agent. These agents divide the complex tasks into manageable sub-steps, enabling LLMs to generate accurate and reliable results at each stage. The case study demonstrates the successful translation of a building description into an error-free EnergyPlus model for the iUnit modular building at the National Renewable Energy Laboratory. The effectiveness of our workflow surpasses: 1) naive prompt engineering, 2) other LLM-based workflows, and 3) manual modeling, in terms of accuracy, reliability, and time efficiency. The paper concludes with a discussion on the interplay between foundational models and LLM agent planning design, advocating for the use of fine-tuned, specialized models to advance this field.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding

Quantum computing calibration depends on interpreting experimental data, and calibration plots provide the most universal human-readable representation for this task, yet no systematic evaluation exists of how well vision-language models (VLMs) interpret them. We introduce QCalEval, the first VLM benchmark for quantum calibration plots: 243 samples across 87 scenario types from 22 experiment families, spanning superconducting qubits and neutral atoms, evaluated on six question types in both zero-shot and in-context learning settings. The best general-purpose zero-shot model reaches a mean score of 72.3, and many open-weight models degrade under multi-image in-context learning, whereas frontier closed models improve substantially. A supervised fine-tuning ablation at the 9-billion-parameter scale shows that SFT improves zero-shot performance but cannot close the multimodal in-context learning gap. As a reference case study, we release NVIDIA Ising Calibration 1, an open-weight model based on Qwen3.5-35B-A3B that reaches 74.7 zero-shot average score.

Cao, Shuxiang↗

DOE OSTI2024

Synergizing human expertise and AI efficiency with language model for microscopy operation and automated experiment design

With the advent of large language models (LLMs), in both the open source and proprietary domains, attention is turning to how to exploit such artificial intelligence (AI) systems in assisting complex scientific tasks, such as material synthesis, characterization, analysis and discovery. Here, we explore the utility of LLMs, particularly ChatGPT4, in combination with application program interfaces (APIs) in tasks of experimental design, programming workflows, and data analysis in scanning probe microscopy, using both in-house developed APIs and APIs given by a commercial vendor for instrument control. We find that the LLM can be especially useful in converting ideations of experimental workflows to executable code on microscope APIs. Beyond code generation, we find that the GPT4 is capable of analyzing microscopy images in a generic sense. At the same time, we find that GPT4 suffers from an inability to extend beyond basic analyses for more in-depth technical experimental design. We argue that an LLM specifically fine-tuned for individual scientific domains can potentially be a better language interface for converting scientific ideations from human experts to executable workflows. Such a synergy between human expertise and LLM efficiency in experimentation can open new doors for accelerating scientific research, enabling effective experimental protocols sharing in the scientific community.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1990

A probe for real-time images of particle beams and their analyses in a merged-beams apparatus

A real-time charged particle beam probe was developed, which can be used both as a beam diagnostic (beam tuning) and to quantitatively determine the three-dimensional density distribution of a beam. The probe consists of a microchannel plate, an aluminized phosphor screen deposited on a fiber-optic faceplate, a flexible fiber-optic bundle, and a charge injection device (CID) in tandem. Digital or analog video output of the CID is fed into a computer or oscilloscope, respectively, for analysis or observation. The probe can be moved continuously along the beams' paths to obtain 'pictures' of the beam at any desired interval, thus giving three-dimensional form factors. The beams, singly or simultaneously, may be observed on the monitor facilitating the task of beam adjustment for optimum overlap. The digital output is used for quantitative computation of the beam overlaps. The device is linear with beam intensity, but the performance degrades with time due to beam damage of the microchannel plate.

Forand, J. L.↗

DOE OSTI2021

Multifunctional Metal–Oxide Nanocomposite Thin Film with Plasmonic Au Nanopillars Embedded in Magnetic La 0.67 Sr 0.33 MnO 3 Matrix

Searching for multifunctional materials with tunable magnetic and optical properties has been a critical task toward the implementation of future integrated optical devices. Vertically aligned nanocomposite (VAN) thin films provide a unique platform for multifunctional material designs. In this work, a new metal–oxide VAN has been designed with plasmonic Au nanopillars embedded in a ferromagnetic La 0.67 Sr 0.33 MnO 3 (LSMO) matrix. Such Au–LSMO nanocomposite presents intriguing plasmon resonance in the visible range and magnetic anisotropy property, which are functionalized by the Au and LSMO phase, respectively. Furthermore, the vertically aligned nanostructure of metal and dielectric oxide results in the hyperbolic property for near-field electromagnetic wave manipulation. Such optical and magnetic response could be further tailored by tuning the composition of Au and LSMO phases.

36 MATERIALS SCIENCE↗

NASA NTRS2004

The Multistage Compressor Facility

Research and developments of new aerospace technologies is one of Glenn Research Center's specialties. One facility that deals with the research of aerospace technologies is the High-speed Multistage Compressor Facility. This facility will be testing the performance and efficiency of an Ultra Efficient Engine Technology (UEET) two-stage compressor. There is a lot of preparation involved with testing something of this caliber. Before the test article can be installed into the test rig, the facility must be fully operational and ready to run. Meaning all the necessary instrumentation must be calibrated and installed in the facility. The test rig should also be in safe operating condition, and the proper safety permits obtained. In preparation for the test, the Multistage Compressor Facility went through a few changes. For instance the facility will now be utilizing slip rings, the gearbox went through some maintenance, new lubrications systems replaced the old ones, and special instrumentation needs to be fine tuned to achieve the maximum amount of accurate data. Slips rings help gather information off of a rotating device - in this case from a shaft - onto stationary contacts. The contacts (or brushes) need to be cooled to reduce the amount of frictional heat produced between the slip ring and brushes. The coolant being run through the slip ring is AK-225, a material hazardous to the ozone. To abide by the safety regulations the coolant must be run through a closed chiller system. A new chiller system was purchased but the reservoir that holds the coolant was ventilated which doesn t make the system truly closed and sealed. My task was to design and have a new reservoir built for the chiller system that complies with the safety guidelines. The gearbox had some safety issues also. Located in the back of the gearbox an inching drive was set up. When the inching drive is in use the gears and chain are bare and someone can easily get caught up in it. So to prevent anyone from getting hurt in the gears I designed a chain guard. Additional information is included in the original extended abstract.

Flegel, Ashlie↗

NASA NTRS2010

Quality Control and Calibration of the Dual-Polarization Radar at Kwajalein, RMI

Weather radars, recording information about precipitation around the globe, will soon be significantly upgraded. Most of today s weather radars transmit and receive microwave energy with horizontal orientation only, but upgraded systems have the capability to send and receive both horizontally and vertically oriented waves. These enhanced "dual-polarimetric" (DP) radars peer into precipitation and provide information on the size, shape, phase (liquid / frozen), and concentration of the falling particles (termed hydrometeors). This information is valuable for improved rain rate estimates, and for providing data on the release and absorption of heat in the atmosphere from condensation and evaporation (phase changes). The heating profiles in the atmosphere influence global circulation, and are a vital component in studies of Earth s changing climate. However, to provide the most accurate interpretation of radar data, the radar must be properly calibrated and data must be quality controlled (cleaned) to remove non-precipitation artifacts; both of which are challenging tasks for today s weather radar. The DP capability maximizes performance of these procedures using properties of the observed precipitation. In a notable paper published in 2005, scientists from the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) at the University of Oklahoma developed a method to calibrate radars using statistically averaged DP measurements within light rain. An additional publication by one of the same scientists at the National Severe Storms Laboratory (NSSL) in Norman, Oklahoma introduced several techniques to perform quality control of radar data using DP measurements. Following their lead, the Topical Rainfall Measuring Mission (TRMM) Satellite Validation Office at NASA s Goddard Space Flight Center has fine-tuned these methods for specific application to the weather radar at Kwajalein Island in the Republic of the Marshall Islands, approximately 2100 miles southwest of Hawaii and 1400 miles east of Guam in the tropical North Pacific Ocean. This tropical oceanic location is important because the majority of rain, and therefore the majority of atmospheric heating, occurs in the tropics where limited ground-based radar data are available.

Marks, David A.↗

NASA NTRS2012

Advisory Algorithm for Scheduling Open Sectors, Operating Positions, and Workstations

Air traffic controller supervisors configure available sector, operating position, and work-station resources to safely and efficiently control air traffic in a region of airspace. In this paper, an algorithm for assisting supervisors with this task is described and demonstrated on two sample problem instances. The algorithm produces configuration schedule advisories that minimize a cost. The cost is a weighted sum of two competing costs: one penalizing mismatches between configurations and predicted air traffic demand and another penalizing the effort associated with changing configurations. The problem considered by the algorithm is a shortest path problem that is solved with a dynamic programming value iteration algorithm. The cost function contains numerous parameters. Default values for most of these are suggested based on descriptions of air traffic control procedures and subject-matter expert feedback. The parameter determining the relative importance of the two competing costs is tuned by comparing historical configurations with corresponding algorithm advisories. Two sample problem instances for which appropriate configuration advisories are obvious were designed to illustrate characteristics of the algorithm. Results demonstrate how the algorithm suggests advisories that appropriately utilize changes in airspace configurations and changes in the number of operating positions allocated to each open sector. The results also demonstrate how the advisories suggest appropriate times for configuration changes.

Bloem, Michael↗

NASA NTRS1995

Implementation of a state of the art automated system for the production of cloud/water vapor motion winds from geostationary satellites

The research objectives in this proposal were part of a continuing program at UW-CIMSS to develop and refine an automated geostationary satellite winds processing system which can be utilized in both research and operational environments. The majority of the originally proposed tasks were successfully accomplished, and in some cases the progress exceeded the original goals. Much of the research and development supported by this grant resulted in upgrades and modifications to the existing automated satellite winds tracking algorithm. These modifications were put to the test through case study demonstrations and numerical model impact studies. After being successfully demonstrated, the modifications and upgrades were implemented into the NESDIS algorithms in Washington DC, and have become part of the operational support. A major focus of the research supported under this grant attended to the continued development of water vapor tracked winds from geostationary observations. The fully automated UW-CIMSS tracking algorithm has been tuned to provide complete upper-tropospheric coverage from this data source, with data set quality close to that of operational cloud motion winds. Multispectral water vapor observations were collected and processed from several different geostationary satellites. The tracking and quality control algorithms were tuned and refined based on ground-truth comparisons and case studies involving impact on numerical model analyses and forecasts. The results have shown the water vapor motion winds are of good quality, complement the cloud motion wind data, and can have a positive impact in NWP on many meteorological scales.

Velden, Christopher↗

NASA NTRSDate not supplied

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.

air traffic management↗

NASA NTRSDate not supplied

Predicting Airport Runway Configuration for Decision-Support Using Supervised Learning

air traffic management↗

DOE OSTI2020

Multi-Node Program Fuzzing on High Performance Computing Resources

Significant effort is placed on tuning the internal parameters of fuzzers to explore the state space, measured as coverage, of binaries. In this work, we investigate the effects of the external environment on the resulting coverage after fuzzing two binaries with AFL for 24 hours. Parameters such as scaling to multiple nodes, node saturation, and parallel file system type on HPC resources are controlled in order to maximize coverage. It will be shown that employing a parallel file system such as IBM's General Parallel File System offers an advantage for fuzzing operations, since it contains enhancements for performance optimization. When combined with scaling to two and four nodes, while simultaneously restricting the number of coordinated AFL tasks per node on the low end (10-50% of available physical cores), coverage may be enhanced within a shorter period of time. Thus, controlling the external environment is a useful effort.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Athena-I CUBIT Journal Files

The Monte Carlo N-Particle (MCNP)1 transport code version 6 (also known as MCNP6) has the capability for tracking particles on unstructured mesh (UM) geometry models embedded into con structive solid geometry (CSG) cells. This feature has been developed for performing calculations of complex geometry models because manually creating CSG models is a time-consuming and error prone process as the complexities of geometries increase. The UM capability was originally designed to work with UM models created with the Abaqus software and ASCII input files that it generates. The MCNP code version 6.0 and later can process UM models formatted as Abaqus input files. Starting with version 6.3, MCNP can also process HDF5 mesh input files. External codes must be used to generate Abaqus input files for MCNP UM calculations. CUBIT, the Sandia National Laboratory automated mesh generation toolkit, can generate a UM model formatted as an Abaqus input file. However, the Abaqus input files exported from CUBIT cannot be used for MCNP simulations because it lacks the proper syntax. A Python script was developed to convert an Abaqus file created by CUBIT to an Abaqus file format that MCNP can process. Creating UM models for complex geometries is not an easy task. The process of creating UM models in CUBIT for MCNP simulations is detailed in. CUBIT provides several user interface options including a graphical user interface (GUI) and a command line interface. A GUI provides an easy way to use CUBIT without learning the CUBIT command syntax. When using CUBIT with either interface option, command lines are written into an ASCII file known as a journal file; this journal file can be edited and archived so that it can be played back in CUBIT to automatically generate a UM model. This report describes the CUBIT journal files of the UM models developed for Athena-I. The Athena platform, an energy-tuning assembly, was developed to spectrally shape the National Ignition Facility (NIF) deuterium-tritium fusion neutron source to a thermonuclear (fusion) plus prompt fission neutron spectrum with capability to act as a short-pulse neutron source. MCNP6 was used for the Athena experiment design analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗