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Results for “prompt engineering”

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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

The Mars climate sounder in-flight positioning anomaly

The paper discusses the Mars Climate Sounder (MCS) instrument’s in-flight positioning errors and presents background material about it. A short overview of the instrument’s science objectives and data acquisition techniques is provided. The brief mechanical description familiarizes the reader with the MCS instrument. Several key items of the flight qualification program, which had a rigorous joint drive test program but some limitations in overall system testing, are discussed. Implications this might have had for the flight anomaly, which began after several months of flawless space operation, are mentioned. The detection, interpretation, and instrument response to the errors is discussed. The anomaly prompted engineering reviews, renewed ground, and some in-flight testing. A summary of these events, including a timeline, is included. Several items of concern were uncovered during the anomaly investigation, the root cause, however, was never found. The instrument is now used with two operational constraints that work around the anomaly. It continues science gathering at an only slightly diminished pace that will yield approximately 90% of the originally intended science.

Kass, David↗
NASA NTRSDate not supplied

Tracking the Hunga Tonga-Hunga Ha’apai Eruption Stratospheric Aerosol and Trace Gas Plumes Using Machine Learning

On January 15, 2022, the Hunga Tonga-Hunga Ha’apai (hereafter, Hunga Tonga) submarine volcano had an explosive eruption that thrusted ash, gases, and water vapor through the troposphere into the stratosphere and mesosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using data retrieved from low earth orbiting satellite instruments (e.g., OMPS, OMI, and CALIPSO), this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), with prompt engineering can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline using NASA Earthdata and Openscapes, establishes a framework for systematically and rapidly studying extreme events, including volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of remote sensing data, this work demonstrates how AI and open science can accelerate research and generate actionable results. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions (e.g., the Atmosphere Observing System (AOS)), and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters and extreme events in a changing world.

David M. Giles↗
DOE OSTI2024

Flame kinetics at scramjet-engine-relevant conditions: Role of prompt dissociation of weakly-bound radicals

Combustion in high-speed ram-based propulsion engines occurs under distinct thermodynamic conditions of high reactant temperatures (greater than 1000 K) and relatively low pressures (<5 atm). There is a lack of fundamental flame measurements at such conditions that result in adiabatic flame temperatures (T ad ) exceeding 2500 K. In this work, we have measured laminar flame speeds of oxygen-enriched CH 4 /oxidizer mixtures at sub-atmospheric conditions to probe kinetics at high T ad using the isobaric spherically expanding flame approach. Simulations with recent kinetic models revealed increasing differences between data and model predictions with increasing T ad , reaching up to 25 %. Kinetic analyses reveal that at the thermodynamic conditions in these O 2 -enriched flames, i.e., lower pressures and higher T ad , the effects of HCO prompt dissociation are accentuated. In addition to HCO, the prompt dissociations of CH 2 OH and C 2 H 5 are also considered. Here, the prompt dissociations of all three radicals were evaluated and their effects considered in flame speed simulations. Reaction path analysis for the present flames revealed that approximately half of the reaction flux for HCO formation undergoes prompt dissociation to H + CO. Furthermore, these analyses also revealed that the pathways and sensitive reactions are similar between oxygen-enriched fuel/oxidizer mixtures and preheated fuel/air mixtures, if both have similar T ad . Thus, flames of oxygen-enriched mixtures could be a surrogate to probe the flame chemistry of highly preheated mixtures at relatively low pressures that are often encountered in ram-based propulsion engine combustors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies

The rapid progression in artificial intelligence has facilitated the emergence of large language models like ChatGPT, offering potential applications extending into specialized engineering modeling, especially physics-based building energy modeling. This paper investigates the innovative integration of large language models with building energy modeling software, focusing specifically on the fusion of ChatGPT with EnergyPlus. A literature review is first conducted to reveal a growing trend of incorporating large language models in engineering modeling, albeit limited research on their application in building energy modeling. We underscore the potential of large language models in addressing building energy modeling challenges and outline potential applications including simulation input generation, simulation output analysis and visualization, conducting error analysis, co-simulation, simulation knowledge extraction and training, and simulation optimization. Three case studies reveal the transformative potential of large language models in automating and optimizing building energy modeling tasks, underscoring the pivotal role of artificial intelligence in advancing sustainable building practices and energy efficiency. The case studies demonstrate that selecting the right large language model techniques is essential to enhance performance and reduce engineering efforts. The findings advocate a multidisciplinary approach in future artificial intelligence research, with implications extending beyond building energy modeling to other specialized engineering modeling.

building energy modeling↗
NASA NTRS2005

Faults Discovery By Using Mined Data

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

Lee, Charles↗
NASA NTRS2006

State Analysis Database Tool

The State Analysis Database Tool software establishes a productive environment for collaboration among software and system engineers engaged in the development of complex interacting systems. The tool embodies State Analysis, a model-based system engineering methodology founded on a state-based control architecture (see figure). A state represents a momentary condition of an evolving system, and a model may describe how a state evolves and is affected by other states. The State Analysis methodology is a process for capturing system and software requirements in the form of explicit models and states, and defining goal-based operational plans consistent with the models. Requirements, models, and operational concerns have traditionally been documented in a variety of system engineering artifacts that address different aspects of a mission s lifecycle. In State Analysis, requirements, models, and operations information are State Analysis artifacts that are consistent and stored in a State Analysis Database. The tool includes a back-end database, a multi-platform front-end client, and Web-based administrative functions. The tool is structured to prompt an engineer to follow the State Analysis methodology, to encourage state discovery and model description, and to make software requirements and operations plans consistent with model descriptions.

Rasmussen, Robert↗
NASA NTRS1995

Droplet Cluster Behavior in Dense and Dilute Regions of a Spray

Concern regarding the efficiency, stability and safety margins of bi-propellant combustion in rocket engines has prompted the investigation of many specific aspects of spray evaporation, ignition and combustion previously not studied. The phenomenology of bi- propellant spray evaporation, ignition and combustion in a highly turbulent environment at elevated pressure is discussed.

liquid rocket propulsion bi-propellant combustion ↗
NASA NTRS1989

Exploratory Study of the Acoustic Performance of Piezoelectric Actuators

The proposed ducted fan engine has prompted the need for increasingly lightweight and efficient noise control devices. Exploratory tests at the NASA Langley Research Center were conducted to evaluate three piezoelectric specimens as possible control transducers: a Polyvinylidene Flouride (PVDF) piezofilm sample and two composite samples of Lead Zirconate Titanate (PZT) rods embedded in fiberglass. The tests measured the acoustic output efficiency and evaluated the noise control characteristics when interacting with a primary sound source. The results showed that a PZT sample could diminish the reflected acoustic waves. However, the PZT acoustic output must increase by several orders of magnitude to qualify as a control transducer for the ducted fan engine.

SantaMaria, O. S.↗
DOE OSTI2025

Leveraging large language models to automate the identification of healthcare access barriers for veterans

Objective: To develop and evaluate an automated system for identifying healthcare barriers focusing on transportation issues in veterans’ clinical notes using large language models (LLMs) and to assess the impact of different prompting strategies on classification performance and explanation consistency. Methods: We developed a hybrid system combining pattern matching for templated notes with LLM analysis for free-text notes. Using 2000 manually annotated clinical notes, we compared four prompting strategies (dual-role short, dual-role long, analysis-first, analysis-only) across Mistral-7B and Llama-3.1 models. We evaluated classification performance using standard metrics and assessed explanation consistency through embedding similarity analysis. Results: The analysis-first strategy achieved superior performance, with Mistral-7B reaching an F1 score of 0.914, outperforming traditional machine learning approaches (GBM: 0.786, BERT: 0.811). LLMs demonstrated higher explanation consistency within models (mean cosine similarity 0.887–0.908) compared to cross-model similarities (0.767–0.872). Pattern matching successfully handled 6.7% of templated notes deterministically. Mistral-7B showed greater internal consistency but higher abstention rates compared to Llama-3.1. Conclusion: Requiring LLMs to analyze evidence before classification improves both accuracy and explanation consistency for identifying transportation barriers in clinical notes. This approach enables automated barrier detection at scale while providing clinically relevant explanations, supporting both population-level healthcare planning and individual patient care decisions.

Healthcare access barriers↗
DOE OSTI2024

Linking Threat Agents to Targeted Organizations: A Pipeline for Enhanced Cybersecurity Risk Metrics

In this study, we present a methodology leveraging Large Language Models (LLMs) to transform Cybersecurity Threat Intelligence (CTI) narratives into actionable insights for individual organizations. Our approach automates the extraction of machine-readable adversary SKRAM (Skills, Knowledge, Resources, Authorities, and Motivation) attributes from open-source reports, extending LLM utility beyond typical interactions. This innovation enables precise, automated assessments of cybersecurity risks posed by various adversaries. Using a chain-of-thought and multi-shot prompting strategy, our methodology advances the automation of cybersecurity feature extraction for new machine-learning models that predict the risk of adversary targeting. This approach is refined using a substantial dataset of over 150 analyst-validated threat reports and synthetic organizational data from 900 companies. Here, by bootstrapping the training data with a rule-based heuristic over synthetic data, we have developed a high-accuracy machine-learning model that allows entities to dynamically prioritize threats and defensive actions.

Cyber Threat Intelligence↗
NASA NTRS2002

Intra-Engine Trace Species Chemistry

Prompted by the needs of downstream plume-wake models, the Massachusetts Institute of Technology (MIT) and Aerodyne Research Incorporated (ART) initiated a collaborative effort, with funding from the NASA AEAP, to develop tools that would assist in understanding the fundamental drivers of chemical change within the intra-engine exhaust flow path. Efforts have been focused on the development of a modeling methodology that can adequately investigate the complex intra-engine environment. Over the history of this project, our research has increasingly pointed to the intra-engine environment as a possible site for important trace chemical activity. Modeling studies we initiated for the turbine and exhaust nozzle have contributed several important capabilities to the atmospheric effects of aviation assessment. These include a more complete understanding of aerosol precursor production, improved initial conditions for plume-wake modeling studies, and a more comprehensive analysis of ground-based test cell and in-flight exhaust measurement data. In addition, establishing a physical understanding of important flow and chemical processes through computational investigations may eventually assist in the design of engines to reduce undesirable species.

Waitz, Ian A.↗
NASA NTRS2009

Towards Co-Engineering Communicating Autonomous Cyber-Physical Systems

In this paper, we sketch a framework for interdisciplinary modeling of space systems, by proposing a holistic view. We consider different system dimensions and their interaction. Specifically, we study the interactions between computation, physics, communication, uncertainty and autonomy. The most comprehensive computational paradigm that supports a holistic perspective on autonomous space systems is given by cyber-physical systems. For these, the state of art consists of collaborating multi-engineering efforts that prompt for an adequate formal foundation. To achieve this, we propose a leveraging of the traditional content of formal modeling by a co-engineering process.

Bujorianu, Marius C.↗
NASA NTRS2012

X-Ray Flare Candidates in Short Gamma-Ray Bursts

We present the first systematic study of X-ray flare candidates in short gamma-ray bursts (SGRBs) exploiting the large 6-year Swift database with the aim to constrain the physical nature of such fluctuations. We find that flare candidates appear in different types of SGRB host galaxy environments and show no clear correlation with the X-ray afterglow lifetime; flare candidates are detected both in SGRBs with a bright extended emission in the soft gamma-rays and in SGRBs which do not show such component. We furthermore show that SGRB X-ray flare candidates only partially share the set of observational properties of long GRB (LGRB) flares. In particular, the main parameter driving the duration evolution of X-ray variability episodes in both classes is found to be the elapsed time from the explosion, with very limited dependence on the different progenitors, environments, central engine life-times, prompt variability time-scales and energy budgets. On the contrary, SGRB flare candidates significantly differ from LGRB flares in terms of peak luminosity, isotropic energy, flare-to-prompt luminosity ratio and relative variability flux. However, these differences disappear when the central engine time-scales and energy budget are accounted for, suggesting that (i) flare candidates and prompt pulses in SGRBs likely have a common origin; (ii) similar dissipation and/or emission mechanisms are responsible for the prompt and flare emission in long and short GRBs, with SGRBs being less energetic albeit faster evolving versions of the long class. Finally, we show that in strict analogy to the SGRB prompt emission, flares candidates fall off the lag-luminosity relation defined by LGRBs, thus strengthening the SGRB flare-prompt pulse connection.

Margutti, R.↗
DOE OSTI2025

Sample glue layer investigation and mitigation for laser induced prompt impulse experiments

Understanding longer timescale material reactions under dynamic stress loading is critical for applications in materials engineering, shock physics, and planetary science. Prompt impulse experiments generate lower pressures since the ablator—the material first removed by the laser—is thicker and farther from the diagnostic plane, capturing aggregate material responses from the initial shock wave, rarefaction waves, and later time effects. This complexity demands thorough material characterization and simulation support. Since traditional sample construction is specific to supported shock experiments, designing prompt impulse experiments requires reconsideration around target design and sample engineering. Here, we present sample preparation techniques, experimental investigations, and theoretical simulations to investigate glue layer impacts, aiming to standardize samples for consistent data at lower laser fluences. We find that glue layers <30 μm have a minimal impact on peak velocity and pulse shape. The peak velocity scales linearly with glue layer thickness until a glue layer of 75 μm. For glue layers >75 μm, the peak velocity no longer scales with thickness; however, the pulse shape continues to degrade as described by simulations.

Lasers↗
NASA NTRS1989

Fluctuating pressures in pump diffuser and collector scrolls, part 1

The cracking of scroll liners on the SSME High Pressure Fuel Turbo Pump (HPFTP) on hot gas engine test firings has prompted a study into the nature of pressure fluctuations in centrifugal pump states. The amplitudes of these fluctuations and where they originate in the pump stage are quantified. To accomplish this, a test program was conducted to map the pressure pulsation activity in a centrifugal pump stage. This stage is based on typical commercial (or generic) pump design practice and not the specialized design of the HPFTP. Measurements made in the various elements comprising the stage indicate that pulsation activity is dominated by synchronous related phenomena. Pulsation amplitudes measured in the scroll are low, on the order of 2 to 7 percent of the impeller exit tip speed velocity head. Significant non-sychronous pressure fluctuations occur at low flow, and while of interest to commercial pump designers, have little meaning to the HPFTP experience. Results obtained with the generic components do provide insights into possible pulsation related scroll failures on the HPFTP, and provide a basis for further study.

Sloteman, Donald P.↗
NASA NTRS2017

Juno Trajectory Redesign Following PRM Cancellation

In October 2016, the Juno spacecraft was operating in 53.5-day capture orbits and final preparations were underway for a Period Reduction Maneuver (PRM) to achieve the planned 14-day science orbits. However, one week before PRM execution, a main engine propulsion system anomaly prompted an indefinite PRM delay and immediate updates to the Juno reference trajectory. This paper outlines stopgap trajectory design activities immediately following PRM delay and longer-term trajectory redesign considerations including various possible PRM epochs, orbit period, longitude grid characteristics, and eclipse avoidance strategies that culminated in the decision to cancel PRM and adopt a new 53-day reference trajectory.

Bordi, John J.↗
NASA NTRS2005

Gamma-ray Bursts: The Prompt Emission

Gamma-ray bursts are the largest explosions in the Universe. The radiation is thought to come from a hypernova initiated from the collapse of a massive star or perhaps the merger of two compact stars such s neutron stars and/or black holes. Most of the observed energy is radiated as gamma rays, usually lasting from a fraction of a second to several hundred seconds. The energy generation process is usually referred to as the "central engine". Observed properties of this prompt emission, including spectra, time profiles and durations will be discussed. The history of these observations and future GRB spacecraft will also be described.

Fishman, Jerry↗
NASA NTRS1993

Study of hydraulic actuation system for Space Shuttle main engine propellant valves

Recent performance concerns involving the Space Shuttle Main Engine Propellant Valve Actuator assemblies prompted the NASA Marshall Space Flight Center to request an independent design assessment. Moog Inc. responded to this request and received a study contract with objectives of increasing valve reliability, decreasing maintenance costs while preserving the existing design interfaces. The results of the Propellant Valve Actuation System review focus on contamination control and the bypass valve design. Three proof of concept bypass valves employing design changes were built and successfully tested. Test results are presented.

Ewel, Bob↗